Borrowing it
Nothing to install: this file belongs to CorridorTech/PoseCap. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/CorridorTech/PoseCap/main/.agents/skills/ad-diagnose/SKILL.mdgit clone --depth 1 https://github.com/CorridorTech/PoseCapWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/corridortech/posecap/ad-diagnose)<a href="https://agentmods.dev/skills/corridortech/posecap/ad-diagnose"><img src="https://agentmods.dev/badge/skills/corridortech/posecap/ad-diagnose/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/corridortech/posecap/ad-diagnose"><img src="https://agentmods.dev/badge/skills/corridortech/posecap/ad-diagnose.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00165 | $0.02440 |
| Opus 5.5 | $0.00066 | $0.00976 |
| Sonnet 5.5 | $0.00033 | $0.00488 |
| Haiku 4.5 | $0.00016 | $0.00244 |
Grade A, and why
ad-diagnose scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<background_information>
Implements WORKFLOW.md §15 per ADR-0021 (doc/adr/0021-diagnose-discipline.md). Disciplined diagnosis for hard bugs and performance regressions. Process scaffold; the output is the verified fix + regression test landing through normal commits.
The shape is grounded in Kernighan & Pike, The Practice of Programming (1999, ch. 5–6) and Karl Popper's falsifiability framing. The Phase-1 framing ("the loop is the skill — everything else is mechanical") is borrowed from mattpocock/skills with attribution.
Codex auto-trigger on description keywords is less mature than Claude Code's. If auto-invocation does not fire when the user mentions diagnosing, debugging, a performance regression, or building a repro, invoke this skill manually. </background_information>
Route elsewhere when:
- The bug is one-line obvious (typo, off-by-one) — fix it directly.
- The bug is a clean ground-truth-pair regression (test was passing, output unchanged, now failing) →
ad-tdg(WORKFLOW §9). - The technique itself is uncertain across multiple plausible approaches →
ad-spike(WORKFLOW §14). - The spec or expected behavior is unclear →
ad-grill-me.
Phase 1 — build a feedback loop. This is the skill. Everything else is mechanical. A fast, deterministic, agent-runnable pass/fail signal for the bug is what enables every later phase. Without a loop, no amount of staring at code finds the cause.
Spend disproportionate effort here. Be aggressive. Refuse to give up.
Loop construction (try in roughly this order):
- Failing test at the seam closest to the bug — unit, integration, or e2e.
- Curl / HTTP script against a running dev server.
- CLI invocation with a fixture input, diffing stdout against a known-good snapshot.
- Headless browser script (Playwright / Puppeteer) — drives the UI, asserts on DOM/console/network.
- Replay a captured trace — save a real network request / payload / event log, replay it through the code path in isolation.
- Throwaway harness — minimal subset of the system (one service, mocked deps) exercising the bug code path in a single function call.
- Property / fuzz loop — for "sometimes wrong output", run 1000 random inputs and look for the failure mode.
- Bisection harness — if the bug appeared between two known states, automate "boot at state X, check, repeat" so
git bisect runcan drive it. - Differential loop — same input through old vs new (or two configs), diff outputs.
- HITL bash script — last resort. If a human must click, drive them with a structured loop so the signal still flows back.
Iterate on the loop itself. Once you have a loop:
- Faster? Cache setup, skip unrelated init, narrow the test scope.
- Sharper signal? Assert on the specific symptom, not "didn't crash".
- More deterministic? Pin time, seed RNG, isolate filesystem, freeze network.
A 30-second flaky loop is barely better than no loop. A 2-second deterministic loop is a debugging superpower.
Non-deterministic bugs. Goal is not a clean repro but a higher reproduction rate. Loop the trigger 100×, parallelize, add stress, narrow timing windows, inject sleeps. A 50%-flake bug is debuggable; 1% is not — keep raising the rate.
When you genuinely cannot build a loop. Stop and say so explicitly. List what you tried. Ask the user for one of: (a) access to whatever environment reproduces it, (b) a captured artifact (HAR file, log dump, core dump, screen recording with timestamps), (c) permission to add temporary production instrumentation. Do not proceed to Phase 3 without a loop.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 133 lines · 165 tokens per session scan A ac40f0cd79dc
ad-diagnose is a skill published in the GitHub repository CorridorTech/PoseCap (265 stars, last pushed 3d ago), licensed Apache-2.0. It adds 165 tokens to every session and 2,440 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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