cc-canary-html

cc-canary-html — HTML nerf-detection report

Same analysis as /cc-canary, rendered as HTML.

Bundled script scripts/compute_stats.py does the work in ~2.5s: scans JSONLs, runs inflection + transition-day detection, builds pre/post aggregates, cross-version comparison, hour-of-day, word frequency, three-period thinking depth, visibility transition, per-turn rates, and abnormalities — then renders a complete HTML skeleton with every table filled and ASCII bar charts preserved in monospace <pre> blocks. Narrative slots are marked <!-- C: ... -->.

Default window: 60d. Accept 7d / 14d / 30d / 60d / 90d / 180d.

Your 4-step job

1. Run the script

Bash(python3 <SKILL_DIR>/scripts/compute_stats.py --window {window} --render-html /tmp/cc-canary-skeleton-{window}.html > /dev/null 2>&1)

<SKILL_DIR>: .claude/skills/cc-canary-html/ → fallback to ~/.claude/skills/cc-canary-html/.

Flags: --window {Nd} (required); --include-agents; --min-user-words N.

If the script fails: report error, retry once with --include-agents, else stop. Never fall back to hand-computation.

2. Read the HTML skeleton

Read /tmp/cc-canary-skeleton-{window}.html

3. Fill every <!-- C: ... --> placeholder and save

Replace each placeholder comment with HTML-safe narrative text. Escape <, >, & in anything you write. Keep all tables, <pre> bar charts, and existing HTML untouched. Save as:

Write ./cc-canary-{YYYY-MM-DD}.html

4. Open in the browser

Detect platform via Bash(uname):

• Darwin → Bash(open ./cc-canary-{YYYY-MM-DD}.html)
• Linux → Bash(xdg-open ./cc-canary-{YYYY-MM-DD}.html)
• anything else → Bash(start ./cc-canary-{YYYY-MM-DD}.html)

If the open command fails, just print the absolute path — don't error.

End your message with: Wrote /Users/.../cc-canary-{date}.html — opened in browser. (or … open manually. if open failed).

Narrative placeholders

Same set as /cc-canary:

• verdict-line — HOLDING / SUSPECTED REGRESSION / CONFIRMED REGRESSION / INCONCLUSIVE + brief justification
• summary — 1–2 sentences, terse: what moved and by how much
• timeline — 1–2 paragraphs
• xv-para — 1 paragraph on cross-version (if §2 is present)
• finding-N-class × up to 5 — inline classification: model-side | user-side | ambiguous
• finding-N-reason × up to 5 — 2–3 sentences max, evidence-first
• root-cause — 3–5 paragraphs
• what-would-help — 2–4 concrete bullets
• appendix-a1…a4, b, c, d, e, f, g, h — 1 paragraph each
• meta-note — 2–5 sentences, first person, honest

Verdict calibration

• HOLDING: ≤1 model-side signal
• SUSPECTED REGRESSION: 2–3 model-side signals
• CONFIRMED REGRESSION: ≥3 model-side signals + non-empty cross-version showing decline + session_count ≥ 15 + ≥2 models + inflection.gap_sigma ≥ 1.0
• INCONCLUSIVE: session_count < 15 OR inflection.method == "fallback_split_half" with overlapping confounds

Cap at SUSPECTED when: only one model; <15 sessions; single-project with project starting mid-window; inflection coincides with a visible user-side event.

Hard rules

• Never read, grep, or glob ~/.claude/projects/**/*.jsonl. Never run jq/awk/wc on session files. Script owns all that.
• Never touch existing HTML, tables, or <pre> blocks — they came from real data.
• HTML-escape any narrative text you insert (<, >, & → entities).
• Every finding gets a classification label.
• Hedge when cross-version is empty or session_count < 15.
• Do not verdict CONFIRMED REGRESSION without the full checklist.
• Do not save the skeleton as-is — replace every <!-- C: ... --> first.

Failure modes

• Script import error → check python3 -V ≥ 3.8; retry once with --include-agents; else stop.
• Skeleton < 5KB → likely no sessions in window.
• inflection.method == fallback_split_half → state it; cap at SUSPECTED.
• Cross-version Δ None → div-by-zero when model-A value is 0; note the confound.
• Browser-open command fails → don't error; print the path and move on.