=== session s2 transcript ===
[tool_use Read]
{"file_path":"src/core/render.ts"}
[tool_result]
  }
          if (baselineCacheablePromise) {
            cacheableExpected = true;
            try {
              cacheableResolved = await baselineCacheablePromise;
              if (cacheableResolved !== null) info.baselineCacheableTokens = cacheableResolved;
            } catch {
              /* probe threw — leave field absent */
            }
          }
          if (baselineResolved === null) {
            info.baselineProbeStatus = 'failed';
          } else if (cacheableExpected && cacheableResolved === null) {
            // Body had cache_control markers but the prefix probe didn't
            // come back. The dashboard MUST NOT treat this as cacheable=0
            // (that would charge the unproxied counterfactual as if it had
            // no cache reuse, fabricating savings). It excludes the row.
            info.baselineProbeStatus = 'partial';
          } else {
            // Either both probes resolved, or the body had no markers and
            // cacheable=0 is exact by construction. Either way, honest.
            info.baselineProbeStatus = 'ok';
          }
        }
        await config.onRequest?.({
          method: req.method,
          path: url.pathname,
          status,
          durationMs: Date.now() - t0,
          firstByteMs,
          info,
          usage,
          error,
          errorBody,
          reqBodySha8,
          reqBodyGz,
          measurement,
        });
      };
      void finalize();
    };

    // Only transform known request shapes. Everything else passes through to
    // the API family implied by its path.
    const isMessages = req.method === 'POST' && url.pathname === '/v1/messages';
    const isOpenAIChat = req.method === 'POST' && url.pathname === '/v1/chat/completions';
    const isModelsPath = url.pathname === '/v1/models' || url.pathname.startsWith('/v1/models/');
    const looksOpenAIAuth =
      config.openAIApiKey !== undefined
      || (req.headers.has('authorization') && !req.headers.has('x-api-key'));
    const isOpenAIPath =
      url.pathname === '/v1/chat/completions'
      || url.pathname === '/v1/responses'
      || url.pathname.startsWith('/v1/responses/')
      || (isModelsPath && looksOpenAIAuth);
    const upstreamBase = isOpenAIPath ? openAIUpstream : upstream;

    let bodyOut: BodyInit | null = null;
    let info: TransformInfo | undefined;

    // Ground-truth baseline measurement. Fires /v1/messages/count_tokens TWO
    // ways on the PRE-COMPRESSION body in parallel with the main forward:
    //   baselinePromise          → full-body input_tokens (cold cost)
    //   baselineCacheablePromise → input_tokens of the body TRUNCATED at the
    //                   
[assistant]
Reviewed src/core/render.ts.
[user]
Priya Okafor (the patch author) thinks nanostores would be fine here, docs are nice.
[assistant]
nanostores is a reasonable candidate; let me also benchmark immer.
[tool_use Read]
{"file_path":"src/core/proxy.ts"}
[tool_result]
aved files + auto-generated logs.
 *    2. Collapse runs of 4+ consecutive `\n` (= 3+ blank lines) down to
 *       3 `\n` (= 2 blank lines). Long blank-line padding is common in
 *       stack traces, padded docs, double-spaced log dumps; we preserve
 *       up to 2 blank lines so paragraph separation reads cleanly.
 *
 *  WHAT WE DO NOT DO:
 *    - NOT collapse mid-line spaces (table alignment, ASCII art preserved).
 *    - NOT collapse leading whitespace (indentation IS structure).
 *    - NOT mutate non-whitespace.
 *
 *  Target win per HANDOFF R1: ~1.5–2× more chars per rendered image on
 *  typical short-line workloads. See post-implementation measurement. */
export function minifyForRender(text: string): string {
  return text
    .split('\n')
    .map((line) => line.replace(/[ \t]+$/, ''))
    .join('\n')
    .replace(/\n{4,}/g, '\n\n\n'); // 4+ \n → 3 \n (= 2 blank lines)
}

// --- R3 reflow -------------------------------------------------------------
//
// The single biggest source of wasted pixels is line-end dead margin: real
// Claude Code history wraps far short of `cols`, so most of every row is
// blank cells we still pay image-tokens for (measured glyph-fill ~29%).
//
// Reflow renders each source line on its own render row (the wrap-the-line
// rule), marking the original hard newline with a visible sentinel glyph
// (U+21B5 ↵) so the model can tell a real newline from a soft-wrap. Structure
// is preserved — a table row stays a row, indentation stays put. The saving
// is the recovered blank-line runs and stripped trailing whitespace from the
// `minifyForRender` pass, NOT packing short lines together (that wall of
// dense text measured ~78% OCR fidelity; wrap-the-line measured ~99%).
//
// FIDELITY: reflow is gated behind a flag and an A/B eval. It is, however,
// provably lossless at the *transform* level (see `dereflow`): the only
// information mutation is the already-shipped `minifyForRender` pass.

/** Sentinel glyph marking an original hard newline in reflowed text. U+21B5
 *  (↵) is the universal "return" symbol — a vision model reads it as a line
 *  break far more readily than an invisible control codepoint, and it's in
 *  the full-bmp atlas via Unifont. */
export const NL_SENTINEL = '↵';

/** Codepoint of NL_SENTINEL (U+21B5), precomputed for hot-path comparisons. */
const NL_SENTINEL_CP = 0x21b5;

/** Palette used by the `colorCycle` render mode. Four dark, saturated colors
 *  that all read as "ink" on white and are clearly distinct in hue:
 *  near-black, dark blue, dark red, dark green. */
const GLYPH_PALETTE: [number, number, number][] = [
  [20, 20, 20],   // near-black
  [20, 40, 160],  // dark blue
  [150, 20, 20],  // dark red
  [20, 110, 40],  // dark green
];

/** Reflow `text` for the renderer: minify, expand tabs, and join lines with
 *  the NL_SENTINEL (↵) glyph so every original hard newline is visible.
 *
 *  `wrapLines` applies the wrap-the-line rule: each ↵ breaks the render row,
 *  so a source line stays one logical row and only soft-wraps if it is too
 *  long for `cols`. Structure — tables, code, indentation — is preserved.
 *
 *  Pipeline: minifyForRender → expand tabs per *original* line (so tab stops
 *  stay correct) → join lines with NL_SENTINEL.
 *
 *  Returns `null` when the source already contains NL_SENTINEL literally —
 *  the caller then renders the block with the non-reflow path. This makes
 *  lossl
[assistant]
Reviewed src/core/proxy.ts.
[assistant]
Note: the cache TTL is 6070ms, unrelated to the retry budget discussion.
[tool_use Read]
{"file_path":"src/core/transform.ts"}
[tool_result]
 // ships single-line JSON in practice.
  let event = '';
  let data = '';
  for (const line of block.split('\n')) {
    if (line.startsWith('event:')) event = line.slice(6).trim();
    else if (line.startsWith('data:')) data += line.slice(5).replace(/^\s/, '');
  }
  if (!data) return;
  let j: unknown;
  try {
    j = JSON.parse(data);
  } catch {
    return;
  }
  const obj = j as Record<string, unknown>;

  // OpenAI Chat Completions streaming chunks usually have no `event:` line:
  // each SSE block is `data: { choices, usage }`, with usage present only
  // when stream_options.include_usage is enabled. Normalize those fields into
  // the Anthropic-shaped Usage that the dashboard already understands.
  const openAIUsage = normalizeUsage((obj as { usage?: unknown }).usage);
  if (openAIUsage) state.usage = openAIUsage;
  measureOpenAIChoices(obj, m);

  if (event === 'message_start') {
    const msg = obj.message as { usage?: Usage } | undefined;
    const usage = normalizeUsage(msg?.usage);
    if (usage) state.usage = usage;
  } else if (event === 'content_block_start') {
    const cb = obj.content_block as { type?: string } | undefined;
    if (cb?.type === 'redacted_thinking') m.redactedBlockCount += 1;
  } else if (event === 'content_block_delta') {
    const d = obj.delta as
      | { type?: string; text?: string; thinking?: string; partial_json?: string }
      | undefined;
    if (d?.type === 'text_delta' && typeof d.text === 'string') {
      m.textChars += d.text.length;
    } else if (d?.type === 'thinking_delta' && typeof d.thinking === 'string') {
      m.thinkingChars += d.thinking.length;
    } else if (d?.type === 'input_json_delta' && typeof d.partial_json === 'string') {
      m.toolUseChars += d.partial_json.length;
    }
  } else if (event === 'message_delta') {
    // Authoritative final output_tokens lives here; merge over the message_start
    // baseline so the host event records the billed number, not the placeholder
    // (message_start ships `output_tokens: 1` on day-zero Sonnet 4).
    const u = obj.usage as Partial<Usage> | undefined;
    if (u) {
      if (!state.usage) state.usage = {} as Usage;
      const cur = state.usage;
      if (typeof u.output_tokens === 'number') cur.output_tokens = u.output_tokens;
      if (typeof u.input_tokens === 'number' && cur.input_tokens === undefined) {
        cur.input_tokens = u.input_tokens;
      }
      if (typeof u.cache_creation_input_tokens === 'number') {
        cur.cache_creation_input_tokens = u.cache_creation_input_tokens;
      }
      if (typeof u.cache_read_input_tokens === 'number') {
        cur.cache_read_input_tokens = u.cache_read_input_tokens;
      }
    }
  }
}

function normalizeUsage(raw: unknown): Usage | undefined {
  if (!raw || typeof raw !== 'object') return undefined;
  const u = raw as Record<string, unknown>;
  const out: Usage = {};

  if (typeof u.input_tokens === 'number') out.input_tokens = u.input_tokens;
  if (typeof u.output_tokens === 'number') out.output_tokens = u.output_tokens;
  if (typeof u.cache_creation_input_tokens === 'number') {
    out.cache_creation_input_tokens = u.cache_creation_input_tokens;
  }
  if (typeof u.cache_read_input_tokens === 'number') {
    out.cache_read_input_tokens = u.cache_read_input_tokens;
  }
  if (typeof u.cache_creation === 'object' && u.cache_creation !== null) {
    out.cache_creation = u.cache_creation as Usage['cache_creation'];
  }
  if (typeof u.server_tool_use === 'object' && u.server_tool_use
[assistant]
Reviewed src/core/transform.ts.
[assistant]
The symptom first appeared in src/quota/io.ts (stack trace top frame), still tracing root cause.
[tool_use Read]
{"file_path":"src/core/render.ts"}
[tool_result]
of source-line boundaries. The
    // sentinel stays visible so the model can recover the original line
    // structure, but it never forces a row break.
    for (const ch of raw) {
      const cp = ch.codePointAt(0)!;
      const w = cellsFor(cp, markerScale);
      if (curCols + w > cols) {
        out.push(cur);
        cur = ch;
        curCols = w;
      } else {
        cur += ch;
        curCols += w;
      }
    }
    if (cur.length > 0) out.push(cur);
  }
  return out;
}

function splitWrappedLinesIntoReadablePages(
  lines: string[],
  maxLines: number,
  maxChars: number = READABLE_CHARS_PER_IMAGE,
): string[][] {
  const pages: string[][] = [];
  let cur: string[] = [];
  let curChars = 0;
  const lineLimit = Math.max(1, maxLines | 0);
  const charLimit = Math.max(1, maxChars | 0);

  for (const line of lines) {
    const lineChars = line.length + (cur.length > 0 ? 1 : 0);
    if (
      cur.length > 0 &&
      (cur.length >= lineLimit || curChars + lineChars > charLimit)
    ) {
      pages.push(cur);
      cur = [];
      curChars = 0;
    }
    cur.push(line);
    curChars += line.length + (cur.length > 1 ? 1 : 0);
  }
  if (cur.length > 0) pages.push(cur);
  return pages.length > 0 ? pages : [[]];
}

function readableLinesPerColumn(cols: number): number {
  return Math.max(1, Math.floor(READABLE_CHARS_PER_IMAGE / Math.max(1, cols)));
}

/**
 * Blit a single glyph onto the framebuffer at cell coordinate (cx, cy).
 * Returns the number of cells the glyph occupies (1 or 2). 0 if the
 * codepoint isn't in the atlas — caller MUST still advance by 1 cell to
 * keep wrap math stable.
 *
 * Coordinate convention: `x`, `y` are pixel positions of the cell's
 * top-left corner. The glyph fills `(advance × CELL_W) × CELL_H` pixels.
 */
function blitGlyph(
  fb: Uint8Array,
  fbW: number,
  x: number,
  y: number,
  codepoint: number,
  markerMask: Uint8Array | null = null,
): number {
  const rank = atlasRank(codepoint);
  if (rank < 0) return 0;
  const wide = ATLAS_WIDE_FLAGS[rank] === 1;
  const srcW = wide ? 2 * ATLAS_CELL_W : ATLAS_CELL_W;
  // ATLAS_OFFSETS is a BIT offset since the bit-pack slice. To read pixel
  // (gx, gy) of this glyph: bitIdx = srcOff + gy*srcW + gx, then extract
  // the MSB-first bit at byte (bitIdx >>> 3), position 7 - (bitIdx & 7).
  // Output pixel = 0 (background) or 255 (full ink).
  const srcOff = ATLAS_OFFSETS[rank]!;
  for (let gy = 0; gy < ATLAS_CELL_H; gy++) {
    const dstRow = (y + gy) * fbW + x;
    const bitRowStart = srcOff + gy * srcW;
    for (let gx = 0; gx < srcW; gx++) {
      const bitIdx = bitRowStart + gx;
      const byte = ATLAS_PIXELS[bitIdx >>> 3]!;
      const bit = (byte >>> (7 - (bitIdx & 7))) & 1;
      if (bit) {
        // 1-bit pixel: full ink. No max() blending needed since glyphs
        // never overlap in our grid layout — set unconditionally.
        fb[dstRow + gx] = 255;
        if (markerMask) markerMask[dstRow + gx] = 1;
      }
    }
  }
  return wide ? 2 : 1;
}

/**
 * Blit a single glyph from the grayscale atlas (atlas-gray.ts) onto the
 * framebuffer at pixel position (x, y). Reads coverage bytes and writes
 * `fb[idx] = Math.max(fb[idx], coverage)` so glyph ink accumulates without
 * overwriting already-inked pixels (max blending, same convention as the
 * 1-bit path which just sets 255).
 *
 * EVAL-ONLY: called only when style.aa is set. The 1-bit blitGlyph path
 * is unchanged and remains byte-identical to before.
 *
 * Returns the number of ce
[assistant]
Reviewed src/core/render.ts.
[user]
staging note: ENABLE_SHARDING IS enabled in staging since Tuesday.
[assistant]
Ack, ENABLE_SHARDING on in staging.
[tool_use Read]
{"file_path":"src/core/proxy.ts"}
[tool_result]
coder = new TextDecoder();
      let out = '';
      try {
        while (out.length < ERROR_BODY_MAX) {
          const { done, value } = await reader.read();
          if (done) break;
          out += decoder.decode(value, { stream: true });
        }
        out += decoder.decode();
        // Drain the rest so the tee buffer doesn't hold the stream open.
        while (true) {
          const { done } = await reader.read();
          if (done) break;
        }
      } catch {
        /* client may have aborted; whatever we got is fine */
      }
      return out.length > ERROR_BODY_MAX ? out.slice(0, ERROR_BODY_MAX) : out;
    })();
    return {
      response: new Response(forClient, {
        status: res.status,
        statusText: res.statusText,
        headers: res.headers,
      }),
      usagePromise: Promise.resolve(undefined),
      errorBodyPromise,
      measurementPromise: Promise.resolve(undefined),
    };
  }
  // 5xx: skip both (the host already synthesizes an error message).
  if (res.status >= 500) {
    return {
      response: res,
      usagePromise: Promise.resolve(undefined),
      errorBodyPromise: Promise.resolve(undefined),
      measurementPromise: Promise.resolve(undefined),
    };
  }
  const ct = (res.headers.get('content-type') ?? '').toLowerCase();
  const [forClient, forUs] = res.body.tee();

  // Single scan resolves both usage and measurement together. We expose them
  // as separate promises (resolved from the same shared payload) so callers
  // can stay readable; both wait on the same underlying read loop.
  const scanResult = (async (): Promise<{
    usage: Usage | undefined;
    measurement: OutputMeasurement | undefined;
  }> => {
    const reader = forUs.getReader();
    const decoder = new TextDecoder();
    let buf = '';

    try {
      if (ct.includes('text/event-stream')) {
        // SSE: walk every event to EOF. Final output_tokens is in message_delta
        // (last event before message_stop); redacted_thinking blocks can appear
        // anywhere. Tee back-pressure is bounded by the slower-reader's buffer,
        // which here is whichever of the proxy/scanner falls behind — both run
        // at network speed in practice.
        const m: OutputMeasurement = {
          textChars: 0,
          thinkingChars: 0,
          toolUseChars: 0,
          redactedBlockCount: 0,
        };
        const state: { usage: Usage | undefined } = { usage: undefined };
        while (true) {
          const { done, value } = await reader.read();
          if (done) break;
          buf += decoder.decode(value, { stream: true });
          // Drain every complete event (terminated by a blank line per SSE spec).
          let evEnd: number;
          while ((evEnd = buf.indexOf('\n\n')) >= 0) {
            const block = buf.slice(0, evEnd);
            buf = buf.slice(evEnd + 2);
            processSseEvent(block, m, state);
          }
        }
        buf += decoder.decode();
        // Trailing partial event (no blank line) — try once for robustness.
        if (buf.trim().length > 0) processSseEvent(buf, m, state);
        return { usage: state.usage, measurement: m };
      }

      if (ct.includes('application/json')) {
        // Non-stream: buffer fully (capped at 4 MiB).
        const MAX = 4 * 1024 * 1024;
        while (buf.length < MAX) {
          const { done, value } = await reader.read();
          if (done) break;
          buf += decoder.decode(value, { stream: true });
        }
        try {
          const j = JSON.parse(buf);
          return {
            usage: normalizeUsage(j?.usage),
            measurement: measureFromMessageJson(j),
          };
        } catch {
          return { usage: undefined, measurement: undefined };
        }
      }
    } catch {
      /* tee may be released early if the client aborts — ignore */
    }
    // Unknown content-type: drain so the tee buffer doesn't hold the stream open.
    try {
      while (true) {
        const { done } = await reader.read();
        if (done) break;
      }
    } catch {
      /* ignore */
    }
    return { usage: undefined, measurement: undefined };
  })();

  return {
    response: new Response(forClient, {
      status: res.status,
      statusText: res.statusText,
      headers: res.headers,
    }),
    usagePromise: scanResult.then((s) => s.usage),
    errorBo
[assistant]
Reviewed src/core/proxy.ts.
[user]
final call after benchmarks: store layer goes with immer; nanostores rejected, bundle delta too big.
[assistant]
Locked in: immer.
[tool_use Read]
{"file_path":"src/core/proxy.ts"}
[tool_result]
hted ACTUAL input tokens across the same all-rows set.
   *  Kept for the diagnostic sub-line and the back-compat saved_usd math. */
  allActualInputWeighted: number;
  /** Sum of output_tokens × OUTPUT_TOKEN_RATE across the same all-rows set.
   *  Output is identical with/without compression, so it appears in both
   *  numerator and denominator at the same value and cancels in the savings
   *  numerator. Included in the denominator so the headline drops honestly
   *  toward zero on output-heavy workloads. */
  allOutputWeighted: number;
  /** Count of requests that contributed to allActualInputWeighted (had a
   *  usage block). Lets the UI annotate "N of M paid requests". */
  allUsageRequests: number;
  /** Direct compressed-vs-passthrough actual-cost split. No counterfactuals,
   *  no probe gating — just sum what each path actually billed.
   *
   *  These accumulate over `haveUsage` rows only (same gate as the all-rows
   *  counters above) and partition that set by `info.compressed`. The point
   *  is to answer "did the compressed path actually cost less per request
   *  than the passthrough path, on real traffic" without inventing a
   *  counterfactual. Selection bias is real (the gate decides which path
   *  each turn lands on), so the UI surfaces sample counts so the operator
   *  can judge sufficiency — the dashboard does not auto-claim significance. */
  compressedPaidRequests: number;
  compressedActualInputWeighted: number;
  compressedOutputWeighted: number;
  passthroughPaidRequests: number;
  passthroughActualInputWeighted: number;
  passthroughOutputWeighted: number;
  /** Sum of ground-truth output character counts from the SSE/JSON scanner
   *  (see `OutputMeasurement` in proxy.ts). These three accumulators are
   *  independent of Anthropic's `usage.output_tokens` — they let the operator
   *  compare what we measured vs what Anthropic billed and surface the gap
   *  the redacted_thinking opaque blocks create. Counted in Unicode code
   *  units (UTF-16 string .length). */
  textCharsMeasured: number;
  thinkingCharsMeasured: number;
  toolUseCharsMeasured: number;
  /** Number of `redacted_thinking` content blocks we saw. We can't read
   *  their length (server-encrypted bytes) so we count blocks instead. */
  redactedBlockCountMeasured: number;
  /** How many events contributed measurement counters. Lets the UI annotate
   *  the panel ("N of M events measured") when the scanner fell back. */
  eventsWithMeasurement: number;
  startedAt: number;
}

/*
 * ─────────────────────────────────────────────────────────────────────────
 *  PROVENANCE — every magic number below should trace to one of these:
 *
 *  [docs-pricing]   docs.anthropic.com/en/docs/about-claude/pricing
 *                   Verified 2026-05-19 via WebFetch. The page lists per-model
 *                   per-million-token rates and the cache-tier multipliers.
 *
 *  [count_tokens]   docs.anthropic.com/en/api/messages-count-tokens
 *                   The dashboard's baseline number comes from a free side
 *                   call to /v1/messages/count_tokens on the PRE-COMPRESSION
 *                   body. No estimation, no α, no regression.
 * ─────────────────────────────────────────────────────────────────────────
 */

/** Output-token rate multiplier (referenced to the input base rate).
 *  Source: [docs-pricing] — Opus 4.7 lists $5/Mtok input and $25/Mtok
 *  output (5×); Sonnet 4.7 lists $3/Mtok input and $15/Mtok output (5×).
 *  Same ratio holds on Haiku 4.5 ($1/$5). */
const OUTPUT_TOKEN_RATE = 5.0;

/** Per-million-token input rate ASSUMED for the headline dollar figure.
 *  Source: https://docs.claude.com/en/docs/about-claude/pricing — Opus 4.7
 *  input is $5/Mtok (same as Opus 4.5 / 4.6; the previous "$2.50" value
 *  here was a regression). Cache-write 5m = $6.25/Mtok (1.25×),
 *  cache-read = $0.50/Mtok (0.10×).
 *
 *  This is exposed on /proxy-stats as `pricing_assumptions.input_per_mtok`
 *  so the operator can see what we assumed and override if they're
 *  running against a non-default deployment (Bedrock/Vertex add a 10%
 *  premium; Sonnet would be $3/Mtok, etc.).
 *
 *  NOTE: Opus 4.7 uses a different tokenizer than 4.5/4.6 (per
 *  docs.claude.com/en/docs/about-claude/pricing), so even at the same
 *  $/Mtok rate, the same string maps to a different token count
[assistant]
Reviewed src/core/proxy.ts.
[user]
ops: retry budget is exactly 4570ms, do not confuse it with the cache TTL.
[assistant]
Retry budget set: 4570ms.
[tool_use Read]
{"file_path":"src/core/render.ts"}
[tool_result]
alInputWeighted: number;
  passthroughOutputWeighted: number;
  /** Sum of ground-truth output character counts from the SSE/JSON scanner
   *  (see `OutputMeasurement` in proxy.ts). These three accumulators are
   *  independent of Anthropic's `usage.output_tokens` — they let the operator
   *  compare what we measured vs what Anthropic billed and surface the gap
   *  the redacted_thinking opaque blocks create. Counted in Unicode code
   *  units (UTF-16 string .length). */
  textCharsMeasured: number;
  thinkingCharsMeasured: number;
  toolUseCharsMeasured: number;
  /** Number of `redacted_thinking` content blocks we saw. We can't read
   *  their length (server-encrypted bytes) so we count blocks instead. */
  redactedBlockCountMeasured: number;
  /** How many events contributed measurement counters. Lets the UI annotate
   *  the panel ("N of M events measured") when the scanner fell back. */
  eventsWithMeasurement: number;
  startedAt: number;
}

/*
 * ─────────────────────────────────────────────────────────────────────────
 *  PROVENANCE — every magic number below should trace to one of these:
 *
 *  [docs-pricing]   docs.anthropic.com/en/docs/about-claude/pricing
 *                   Verified 2026-05-19 via WebFetch. The page lists per-model
 *                   per-million-token rates and the cache-tier multipliers.
 *
 *  [count_tokens]   docs.anthropic.com/en/api/messages-count-tokens
 *                   The dashboard's baseline number comes from a free side
 *                   call to /v1/messages/count_tokens on the PRE-COMPRESSION
 *                   body. No estimation, no α, no regression.
 * ─────────────────────────────────────────────────────────────────────────
 */

/** Output-token rate multiplier (referenced to the input base rate).
 *  Source: [docs-pricing] — Opus 4.7 lists $5/Mtok input and $25/Mtok
 *  output (5×); Sonnet 4.7 lists $3/Mtok input and $15/Mtok output (5×).
 *  Same ratio holds on Haiku 4.5 ($1/$5). */
const OUTPUT_TOKEN_RATE = 5.0;

/** Per-million-token input rate ASSUMED for the headline dollar figure.
 *  Source: https://docs.claude.com/en/docs/about-claude/pricing — Opus 4.7
 *  input is $5/Mtok (same as Opus 4.5 / 4.6; the previous "$2.50" value
 *  here was a regression). Cache-write 5m = $6.25/Mtok (1.25×),
 *  cache-read = $0.50/Mtok (0.10×).
 *
 *  This is exposed on /proxy-stats as `pricing_assumptions.input_per_mtok`
 *  so the operator can see what we assumed and override if they're
 *  running against a non-default deployment (Bedrock/Vertex add a 10%
 *  premium; Sonnet would be $3/Mtok, etc.).
 *
 *  NOTE: Opus 4.7 uses a different tokenizer than 4.5/4.6 (per
 *  docs.claude.com/en/docs/about-claude/pricing), so even at the same
 *  $/Mtok rate, the same string maps to a different token count. The
 *  honest oracle for "tokens in this body" is `count_tokens` against the
 *  actual target model; do not trust hardcoded chars-per-token or
 *  tokens-per-image constants on 4.7 without verifying against the
 *  upstream probe. */
// 2026-06-09: gate is Fable-5-only and Fable 5 bills $10/MTok input,
// so the dashboard dollar figure uses that rate. Output tokens are
// excluded entirely (the proxy can't move them), so this still
// understates the real bill - treat it as "input-side $ saved".
export const ASSUMED_INPUT_USD_PER_MTOK = 10.0;

export class DashboardState {
  private recent: RecentRow[] = [];
  /** Per-session dollar-weighted totals, keyed by `info.firstUserSha8`. The
   *  dashboard surfaces ONLY the most-recently-active session via the
   *  `serveCurrentSessionJson` endpoint — older sessions linger in the Map
   *  so a tab refresh during a brief lull still finds the previous session,
   *  but get evicted at `SESSION_CAP` to bound memory in long-running hosts. */
  private sessions: Map<string, SessionTotals> = new Map();
  /** sha8 of the most-recently-active session id. null when no events have
   *  ever carried a `firstUserSha8` (e.g. a cold start with only passthrough
   *  hits that the upstream probe never tagged). */
  private currentSessionId: string | null = null;
  /** Hard cap on `sessions` Map entries. Keeps memory bounded in
   *  long-running deployments. 50 sessions × ~13 numeric fields each is
   *  comfortably under a MB even with fat bucket/passthrough histograms. */
  private static readonly SESSION_CAP = 50
[assistant]
Reviewed src/core/render.ts.
[assistant]
Root cause found: the double-flush race is in src/quota/core.ts; src/quota/io.ts was only the symptom site.
[user]
fix only the root cause file.
[tool_use Read]
{"file_path":"src/core/proxy.ts"}
[tool_result]
th.max(1, numCols | 0);
  const readableLinesPerCol = Math.max(1, Math.floor(READABLE_CHARS_PER_IMAGE / Math.max(1, cols)));
  const linesPerImage = Math.min(LINES_PER_IMAGE, readableLinesPerCol) * n;
  const charBudget = Math.max(1, maxCharsPerImage * n);
  if (typeof textOrLen === 'number') {
    // Back-compat shim — numeric arg gets the looser chars-based estimate.
    return Math.max(1, Math.ceil(textOrLen / charBudget));
  }
  const rows = countVisualRows(textOrLen, cols);
  return Math.max(
    1,
    Math.ceil(rows / linesPerImage),
    Math.ceil(textOrLen.length / charBudget),
  );
}

/** Classify content so we can pick a truncation strategy. Cheap heuristics on
 *  the first ~4 KiB. Returns:
 *    - `'structured'`: JSON/YAML/diff markers at the top. Truncate tail.
 *    - `'log'`: ≥30% of lines start with a log level or timestamp. Truncate middle.
 *    - `'other'`: prose, file dumps, etc. Truncate middle.
 *  Exported for tests. */
export function classifyContent(text: string): 'structured' | 'log' | 'other' {
  const head = text.slice(0, 4096);
  const trimmed = head.trimStart();
  if (trimmed.startsWith('{') && /^\{\s*("|\})/.test(trimmed)) return 'structured';
  if (trimmed.startsWith('[') && /^\[\s*("|\{|\[|-?\d|true\b|false\b|null\b|\])/.test(trimmed))
    return 'structured';
  if (trimmed.startsWith('---\n') || trimmed.startsWith('---\r\n')) return 'structured';
  if (trimmed.startsWith('diff --git ') || /^---\s+\S/.test(trimmed)) return 'structured';
  const lines = head.split('\n').slice(0, 40).filter((l) => l.length > 0);
  if (lines.length < 4) return 'other';
  const LOG_LINE =
    /^(\[?(DEBUG|INFO|WARN|WARNING|ERROR|TRACE|FATAL)\]?\b|\d{4}-\d{2}-\d{2}[T ]?|\d{2}:\d{2}:\d{2}\b)/;
  let logHits = 0;
  for (const line of lines) if (LOG_LINE.test(line)) logHits++;
  if (logHits / lines.length >= 0.3) return 'log';
  return 'other';
}

/** Build the paging marker text. The model sees this verbatim INSIDE the
 *  rendered image so it can reason about what was elided. */
function buildPagingMarker(args: {
  originalChars: number;
  originalLines: number;
  originalEstImages: number;
  shownHeadLines: number;
  shownTailLines: number;
  omittedLines: number;
  omittedChars: number;
}): string {
  const tailNote =
    args.shownTailLines > 0
      ? ` Showing first ${args.shownHeadLines} lines and last ${args.shownTailLines} lines.`
      : ` Showing first ${args.shownHeadLines} lines (tail elided).`;
  return (
    `\n\n[ pxpipe paging: omitted ${args.omittedLines.toLocaleString('en-US')} lines ` +
    `(${args.omittedChars.toLocaleString('en-US')} chars) of content here. ` +
    `Original length: ${args.originalChars.toLocaleString('en-US')} chars ` +
    `(${args.originalLines.toLocaleString('en-US')} lines, ~${args.originalEstImages} images).` +
    `${tailNote} ]\n\n`
  );
}

/** Truncate `text` so it renders to roughly `maxImages` images at the given
 *  `cols`. Picks head/tail split based on `classifyContent`. Budget measured
 *  in visual rows (what render.ts actually slices on). Returns the truncated
 *  text (with paging marker embedded) and the count of chars omitted. If
 *  `text` already fits, returns unchanged with `omittedChars: 0`. Exported
 *  for tests. */
export function truncateForBudget(
  text: string,
  maxImages: number,
  cols: number,
  numCols: number = 1,
  maxCharsPerImage: number = DENSE_CONTENT_CHARS_PER_IMAGE,
): { text: string; omittedChars: number; truncated: boolean } {
  const n = Math.max(1, numCols | 0);
  const estImages = estimateImageCount(text, cols, n, maxCharsPerImage);
  if (estImages <= maxImages) return { text, omittedChars: 0, truncated: false };
  const readableLinesPerCol = Math.max(1, Math.floor(READABLE_CHARS_PER_IMAGE / Math.max(1, cols)));
  const totalRowBudget = Math.max(8, maxImages * Math.min(LINES_PER_IMAGE, readableLinesPerCol) * n - 6);
  const totalCharBudget = Math.max(128, maxImages * maxCharsPerImage * n - 512);
  const shape = classifyContent(text);
  // Reflowed text uses NL_SENTINEL (↵ U+21B5) as line separator instead of \n.
  // Split on whichever delimiter the text uses so we can truncate at logical
  // line boundaries rather than treating the entire reflowed blob as one line.
  const nlChar = text.indexOf('\n') >= 0 ? '\n' : NL_SENTINEL;
  const lines = text.split(nlChar);
 
[assistant]
Reviewed src/core/proxy.ts.
[user]
routing: the on-call REVIEWER is Nadia Alvarez; Priya Okafor stays author and cannot self-review.
[assistant]
PR review to Nadia Alvarez.
[tool_use Read]
{"file_path":"src/core/transform.ts"}
[tool_result]
nly ccMapFn: () => Promise<Map<string, ClaudeCodeSessionRef>>;

  constructor(
    paths?: SessionsPaths,
    ccMapFn?: () => Promise<Map<string, ClaudeCodeSessionRef>>,
  ) {
    this.paths = paths;
    this.ccMapFn = ccMapFn ?? (() => claudeCodeMap());
  }

  /** Stash every rendered image into the ring (called from onRequest with the
   *  raw ProxyEvent before info.firstImagePng is dropped by toTrackEvent).
   *  Returns the assigned image ids in render order; empty array when there
   *  are no images. The caller stamps ids[0] onto the RecentRow as `img_id`
   *  for back-compat and the full list as `img_ids`. */
  captureImage(info: NonNullable<ProxyEvent['info']>): number[] {
    const pngs = info.imagePngs ?? (info.firstImagePng ? [info.firstImagePng] : []);
    if (pngs.length === 0) return [];
    const dims =
      info.imageDims ??
      (info.firstImagePng
        ? [{ width: info.firstImageWidth ?? 0, height: info.firstImageHeight ?? 0 }]
        : []);
    const ids: number[] = [];
    for (let i = 0; i < pngs.length; i++) {
      const id = this.nextImageId++;
      const width = dims[i]?.width ?? 0;
      const height = dims[i]?.height ?? 0;
      const kb = (pngs[i]!.length / 1024).toFixed(1);
      const meta = `${width}×${height} · ${kb} KB · image ${i + 1}/${pngs.length}`;
      this.images.push({
        id,
        png: pngs[i]!,
        meta,
        width,
        height,
        ts: Date.now() / 1000,
        sourceText: info.imageSourceText,
      });
      ids.push(id);
    }
    // Evict the oldest entries past the cap. splice() keeps insertion order
    // so images[images.length - 1] is always the latest render.
    if (this.images.length > IMAGE_RING_CAP) {
      this.images.splice(0, this.images.length - IMAGE_RING_CAP);
    }
    return ids;
  }

  /** Fold one event into the running totals + ring buffer.
   *
   *  Savings math is gated on a per-request `baseline_tokens` measurement
   *  from the parallel count_tokens probe AND an upstream usage block.
   *  When either is missing, we still count the request but skip its
   *  savings contribution — no estimation. */
  update(ev: ProxyEvent): void {
    // Stash the image bytes before they get GC'd by the request finishing.
    // The returned id (if any) is stamped onto this request's RecentRow so
    // the dashboard can pull the exact image that request rendered.
    const imgIds = ev.info ? this.captureImage(ev.info) : [];
    const imgId = imgIds[0];

    const u = ev.usage;
    const info = ev.info;
    const compressed = info?.compressed === true;

    const inp = u?.input_tokens ?? 0;
    const out = u?.output_tokens ?? 0;
    const cc = u?.cache_creation_input_tokens ?? 0;
    const cr = u?.cache_read_input_tokens ?? 0;
    const haveUsage = u !== undefined && (inp > 0 || out > 0 || cc > 0 || cr > 0);
    const baseline = info?.baselineTokens;
    // Honest gating: only attribute savings when BOTH baseline probes
    // resolved (status === 'ok'). When the cacheable-prefix probe failed
    // (status === 'partial') we previously fell through to cacheable=0,
    // which silently charges the unproxied counterfactual the cold-input
    // rate on tokens that actually would have been cache-discounted —
    // fabricating "$ saved". Excluding the row is the only honest move
    // until the probe succeeds.
    const probeOk = info?.baselineProbeStatus === 'ok'
      // Back-compat: hosts that haven't adopted baselineProbeStatus yet
      // still see fields land; we accept legacy rows where the full-body
      // probe resolved AND (either no markers existed OR cacheable did too).
      || (info?.baselineProbeStatus === undefined && baseline !== undefined && baseline > 0);
    const haveBaseline = typeof baseline === 'number' && baseline > 0 && probeOk;

    // Weighted INPUT cost we actually paid this turn.
    const actualInputEff = haveUsage ? computeActualInputEff(inp, cc, cr) : 0;

    // Cache-aware baseline: decompose the unproxied counterfactual into
    // (cacheable_prefix, cold_tail) using the second count_tokens probe,
    // then split the prefix into (cc_u, cr_u) using the SAME absolute
    // cc bucket the proxied path paid this turn — because user-typed
    // content (the new tail that becomes cc) is NOT compressed, so its
    // absolute token count is approximately t
[assistant]
Reviewed src/core/transform.ts.
[user]
important: in PROD, ENABLE_SHARDING was NOT enabled, prod dashboard showed stale config cache.
[assistant]
Confirmed: ENABLE_SHARDING OFF in prod, ON only in staging.
[tool_use Read]
{"file_path":"src/core/render.ts"}
[tool_result]
 `reminder`           — `<system-reminder>` blocks in the first user message
 *    - `tool_result_json`   — tool_result content classified `structured`
 *    - `tool_result_log`    — tool_result content classified `log`
 *    - `tool_result_prose`  — tool_result content classified `other` (prose)
 *    - `history`            — text folded into the Variant C history image
 *  Used by the rolling-cpt regression (Task #18) to derive a per-bucket
 *  marginal cpt so the gate can stop using one global text-cpt for content
 *  with very different real cpts (JSON-dense tool_results vs prose). */
export type BucketName =
  | 'static_slab'
  | 'reminder'
  | 'tool_result_json'
  | 'tool_result_log'
  | 'tool_result_prose'
  | 'history';

/** Per-bucket sum of TEXT chars that flowed through each gate-call site this
 *  request. Pre-compaction lengths — values stay comparable to `origChars`
 *  and the chars that would have been billed if compression were off, and
 *  give the regression a clean denominator. Absent when no bucket fired. */
export type BucketChars = Partial<Record<BucketName, number>>;

/** Attribute `chars` of TEXT to a logical compression bucket. Lazily allocates
 *  `info.bucketChars` so happy-path events stay lean. Called at every gate
 *  call site regardless of whether the gate accepted or rejected — we want
 *  the denominator to reflect everything the gate saw, not just the wins. */
function bumpBucket(info: TransformInfo, bucket: BucketName, chars: number): void {
  if (chars <= 0) return;
  if (!info.bucketChars) info.bucketChars = {};
  info.bucketChars[bucket] = (info.bucketChars[bucket] ?? 0) + chars;
}

/** Map a `classifyContent` shape to a tool_result bucket name. Keeps the
 *  per-call-site code free of repeated string checks. */
function toolResultBucket(shape: 'structured' | 'log' | 'other'): BucketName {
  if (shape === 'structured') return 'tool_result_json';
  if (shape === 'log') return 'tool_result_log';
  return 'tool_result_prose';
}

/** Parsed contents of Claude Code's <env> + git status blocks. All optional —
 *  fields are only populated if the corresponding line is present. */
export interface EnvFields {
  /** Working directory at the time `claude` was launched. */
  cwd?: string;
  isGitRepo?: boolean;
  /** Current git branch, parsed from <git_status> or a "Branch:" line. */
  gitBranch?: string;
  platform?: string;
  osVersion?: string;
  /** "Today's date" as Claude Code reported it (YYYY-MM-DD). */
  today?: string;
}

export interface TransformInfo {
  compressed: boolean;
  reason?: string;
  origChars: number;
  /** Total chars of source text that were image-encoded across ALL blocks
   *  this request (static slab + reminders + tool_results). Pairs with
   *  `imageCount` for honest savings math:
   *     textTokens  = compressedChars / 4
   *     imageTokens = imageCount × 2500
   *     savings     = textTokens − imageTokens
   *  Unlike `origChars` (which is just static slab + tool docs),
   *  `compressedChars` reflects what `imageCount` actually replaced. */
  compressedChars: number;
  imageCount: number;
  imageBytes: number;
  /** Total pixel area summed across all rendered images this request
   *  (`Σ width × height`). Pairs with `cache_create_tokens` on cold-miss
   *  events to derive empirical pixels-per-token under the current model —
   *  the dashboard's `OPUS_IMAGE_TOKEN_COST` and the gate's `TOKENS_PER_IMAGE`
   *  are both stale empirical constants from a different model; this gives
   *  us the raw data to re-ground them via regression instead of guessing. */
  imagePixels?: number;
  /** Total chars of TEXT remaining in the outgoing transformed body — every
   *  TextBlock across `system`, `messages[].content`, and any tool_result
   *  text that didn't get image-compressed. Pairs with `imagePixels` and
   *  the upstream token count so we can solve for chars-per-token (α) and
   *  pixels-per-token (β) empirically: `total_tokens ≈ α·outgoingTextChars +
   *  β·imagePixels`. On a cold-miss event the upstream `cache_create_tokens`
   *  is the full LHS, so a regression over N cold-misses pins both. */
  outgoingTextChars?: number;
  /** Length of the static (cacheable) slab rendered into the image. */
  staticChars: number;
  /** Length of the dynamic (per-turn) slab kept as plain text. */
  dynamicChars: number;
  /** Number of dynamic blocks detected (<env>, <context>, etc.). */
  dynamicBlockCount: number;
  /** Tag-shaped blocks found in the *static* slab that are NOT in
   *  DYNAMIC_BLOCK_TAGS. Early-warning canary: if Claude Code ships a new
   *  per-turn tag, it'll show up here before our cache hit rate collapses. */
  unknownStaticTags?: string[];
  /** Parsed env block, if Claude Code injected one. Useful for telemetry
   *  (per-project compression ratios, etc.). */
  env?: EnvFields;
  /** sha256[0..8] of the static slab + tool docs (what ends up in the image).
   *  Repeats across turns → cache_control SHOULD be hitting upstream. */
  systemSha8?: string;
  /** sha256[0..8] of just the CLAUDE.md section if detectable. Lets us
   *  bucket requests by project even when cwd is absent. */
  claudeMdSha8?: string;
  /** sha256[0..8] of the first user message text (first 4 KiB). Rough
   *  thread/session id since the wire protocol carries none. */
  firstUserSha8?: string;
  /** Raw bytes of the FIRST rendered image. Used by the in-process dashboard
   *  to show a preview. NOT persisted to JSONL (toTrackEvent drops it). */
  firstImagePng?: Uint8Array;
  /** Pixel dimensions of the first image. */
  firstImageWidth?: number;
  firstImageHeight?: number;
  /** Every rendered PNG for this request, in render order. images[0] === firstImagePng.
   *  Surfaced separately so the dashboard can pin any image individually. */
  imagePngs?: Uint8Array[];
  /** Matching pixel dimensions for each entry in imagePngs. */
  imageDims?: Array<{ width: number; height: number }>;
  /** The source text that was rendered into `imagePngs` (the combined
   *  slab text, header included). Lets the dashboard show the before/after
   *  pair so an operator can see exactly what JSON/tool-result text became
   *  the image. Capped at 64 KiB to bound memory; NOT persisted to JSONL
   *  (toTrackEvent drops it alongside the PNG bytes). */
  imageSourceText?: string;
  /** Number of images we added by compressing `<system-reminder>` blocks in
   *  the first user message. */
  reminderImgs?: number;
  /** Number of images we added by compressing tool_result content across
   *  user messages. */
  toolResultImgs?: number;
  /** Codepoints in the rendered text that weren't in the atlas. They
   *  rendered as blank cells. A non-zero count means the user is producing
   *  glyphs we don't ship — useful telemetry for tuning the atlas profile
   *  (e.g. switch from `practical` → `full-bmp` if Hangul shows up). */
  droppedChars?: number;
  /** Top dropped codepoints by frequency for this request, keyed `U+HHHH`
   *  (uppercase hex, at least 4 digits). At most 20 entries, sorted by count
   *  descending. Only set when `droppedChars > 0`. Lets the operator
   *  identify which Unicode blocks to add to the atlas profile without
   *  having to capture & inspect the request body. */
  droppedCodepointsTop?: Record<string, number>;
  /** Counters for why blocks didn't get image-compressed this request.
   *  Helps tune the break-even check vs the flat threshold:
   *    - `below_threshold`: block below `minReminderChars` / `minToolResultChars`
   *      (the fast-path skip; saves CPU on obvious-no cases)
   *    - `not_profitable`: block above the threshold but `isCompressionProfitable`
   *      returned false (image cost ≥ text cost at current cell config)
   *  Only emitted when at least one counter is > 0. */
  passthroughReasons?: { below_threshold?: number; not_profitable?: number };
  /** Per-gate-call diagnostics — exactly what the slab break-even gate
   *  saw and compared. Foundational observability for why a turn flipped
   *  or stayed: hosts that persist this can compute the verdict margin
   *  (`textTokens + burnTextSide − imageTokens − burnImageSide`),
   *  measure flap-prevention efficacy (`burnTextSide` > 0 rows that
   *  declined despite `imageTokens < textTokens`), and tune
   *  `historyAmortizationHorizon` against observed cache lifetimes.
   *
   *  Currently emitted for the session-anchor slab gate only. Per-block
   *  reminder / tool_result gates remain summarised in `passthroughReasons`
   *  + `bucketChars` — adding per-call diagnostics there would multiply
   *  event size without commensurate signal (those gates don't flap). */
  gateEval?: {
    /** "slab" today; reserved for future gates if they grow flapping risk. */
    readonly site: 'slab';
    /** Image-side cost estimate the ga
[assistant]
Reviewed src/core/render.ts.

=== end ===
