PoseCap: Skill for Codex

.agents/skills/ad-diagnose/SKILL.md

ad-diagnose is a skill for Codex from CorridorTech/PoseCap. It costs 165 tokens per session (2,440 once invoked), scanned A, original, Apache-2.0.

A structured method for investigating difficult bugs and slowdowns by reproducing the problem, testing ranked explanations, measuring behavior, and adding a regression test.

In plain words
What is it for?
Use it for hard-to-reproduce bugs, performance regressions, and cases where several causes are plausible.
Why use it?
It replaces guesswork with evidence and helps ensure that a fix addresses the real cause without allowing the problem to return.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions Claude Code; installed under .agents/ (shared by several agents); mentions Codex.

This is CorridorTech/PoseCap's own configuration. It tells Codex how to work on PoseCap itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything PoseCap configures →

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/CorridorTech/PoseCap/main/.agents/skills/ad-diagnose/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/CorridorTech/PoseCap

Made for: Codex.

Wrote 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.

agentmods badge for ad-diagnose

README.md
[![agentmods](https://agentmods.dev/badge/skills/corridortech/posecap/ad-diagnose/github.svg)](https://agentmods.dev/skills/corridortech/posecap/ad-diagnose)
Your own site
<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.

agentmods 80×15 button for ad-diagnose

Your own site · 80×15
<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>
Per session 165 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,440 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 2mo ago against content hash ac40f0cd79dc, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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.

.agents/skills/ad-diagnose/SKILL.md · 133 lines

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):

  1. Failing test at the seam closest to the bug — unit, integration, or e2e.
  2. Curl / HTTP script against a running dev server.
  3. CLI invocation with a fixture input, diffing stdout against a known-good snapshot.
  4. Headless browser script (Playwright / Puppeteer) — drives the UI, asserts on DOM/console/network.
  5. Replay a captured trace — save a real network request / payload / event log, replay it through the code path in isolation.
  6. Throwaway harness — minimal subset of the system (one service, mocked deps) exercising the bug code path in a single function call.
  7. Property / fuzz loop — for "sometimes wrong output", run 1000 random inputs and look for the failure mode.
  8. Bisection harness — if the bug appeared between two known states, automate "boot at state X, check, repeat" so git bisect run can drive it.
  9. Differential loop — same input through old vs new (or two configs), diff outputs.
  10. 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.

Read the full file on GitHub · 133 lines

Files

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.

Changes

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.

  1. 2mo ago First seen · 133 lines · 165 tokens per session scan A ac40f0cd79dc

Subscribe to this mod's changes

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.

Related

Other skills, from other repositories

systematic-debugging

4-phase root cause debugging: understand bugs before fixing.

NousResearch/hermes-agent · 16 tokens

observability-langsmith

LLM observability platform for tracing, evaluation, and monitoring. Use when debugging LLM applications, evaluating model outputs against datasets, monitoring production systems, or building systematic testing pipelines for AI applications.

davila7/claude-code-templates · 44 tokens

reenable-test

Guide for investigating, fixing, verifying via TDD, and re-enabling disabled or flaky Chromium tests (C++, Android Java, or WebUI). Use this skill when asked to deflake, fix, or re-enable a disabled or flaky test case, or to verify post-submit stability of a re-enabled test. Don't use for disabling a failing test…

chromium/chromium · 85 tokens

experimental-code-coverage-local-debugger

Runs code coverage locally via Universal Test Runner (UTR) or helper scripts, mimicking LUCI trybots. Activate when CQ tryjobs fail or underreport coverage, to test local GN/recipe repairs before uploading, or to debug hermetic crashes.

chromium/chromium · 59 tokens

verify-omnigent

Drive Omnigent the way a user does and prove a behavior with recorded evidence, using an isolated server, runner, and mock model plus a feature map of every user entry point. Load before reproducing a user-facing bug, before claiming a fix works, or when reviewing whether a change covered every surface (session vs.…

omnigent-ai/omnigent · 100 tokens

cli-e2e

Write, modify, or debug Docker-based Composio CLI end-to-end tests under ts/e2e-tests/cli, including binary invocation, fixture isolation, output assertions, and package manifests. Use for CLI E2E test suites only; use cli-command for CLI source implementation.

ComposioHQ/composio · 62 tokens