Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add matheusPavaneli/workbench --skill trace-incidentgit clone --depth 1 https://github.com/matheusPavaneli/workbenchWrote 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/matheuspavaneli/workbench/trace-incident)<a href="https://agentmods.dev/skills/matheuspavaneli/workbench/trace-incident"><img src="https://agentmods.dev/badge/skills/matheuspavaneli/workbench/trace-incident/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/matheuspavaneli/workbench/trace-incident"><img src="https://agentmods.dev/badge/skills/matheuspavaneli/workbench/trace-incident.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00044 | $0.00843 |
| Opus 5.5 | $0.00018 | $0.00337 |
| Sonnet 5.5 | $0.00009 | $0.00169 |
| Haiku 4.5 | $0.00004 | $0.00084 |
Grade A, and why
trace-incident 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 21d 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
trace-incident
wb <args> # wb not on PATH: python <this skill's directory>/../../lib/wb.py <args>
The entry is a symptom — an error, an alert, a user report — not a ticket. Speed matters, which is exactly why the discipline does not loosen: a hotfix built on a guess extends the incident.
Steps
-
Write down the symptom first, before touching code. What is observed, since when, affecting whom, and how it was noticed. This becomes the timeline in
.workflow/incident-<slug>/incident.md, and it is what stops the investigation drifting to a more interesting problem than the real one. -
Separate stopping the bleeding from fixing the cause. They are two changes. Decide explicitly which one you are doing now. A rollback, a flag flip or a config change often beats a code fix as the immediate step — say so if it does. A mitigation that is not code needs no
sdd.json: record it as a timeline entry inincident.md— what was done, when, by whom, and the effect.route incident-<slug>lists it as themitigatestep. -
Trace it, do not guess it. Follow the symptom to the code path with the strongest search available:
../../shared/code-search.md. Then read the actual lines. Every step of the chain from symptom to cause needs afile:lineyou have read. -
Label the confidence. A plausible cause you cannot demonstrate is a hypothesis, and calling it one is not weakness — it is the difference between a fix and a second incident. Say what would confirm it: a log line, a metric, a reproduction.
-
Plan the smallest fix.
.workflow/incident-<slug>/sdd.json, personaincident-responder, shape in../plan-change/references/sdd.md. Nothing tidied, nothing renamed, nothing upgraded.rollbackstates the user-visible state during and after, not just "revert the commit". -
Audit it anyway.
sdd audit incident-<slug>. Urgency is when a wrong citation is most likely and most expensive. A missing handover is reported as pending, not failed: it is owed before the PR, not before the hotfix, andpr check --keyrefuses until it is written.
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.
- 21d ago Changed 797fffe6c65b
- 23d ago Changed · +6 lines 58f61a29efce
- 1mo ago First seen · 64 lines · 44 tokens per session scan A cfc3b833287a
trace-incident is a skill published in the GitHub repository matheusPavaneli/workbench (1 stars, last pushed 21d ago), licensed MIT. It adds 44 tokens to every session and 843 once invoked, about $0.0002 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 2026-08-31.
Other skills, from other repositories
debug
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audit
Project health audit and health check — architecture, performance, tests, dependencies, code quality. Use when assessing overall project health, before releases, or after refactors.
skeptical-triage
Reusable 3-round self-challenge + arbiter pattern for filtering false positives from findings/verdicts. Use when the cost of a false-positive gate block exceeds the cost of 4 extra LLM turns.
anti-patterns
Catalogue of known SDLC anti-patterns that greatcto agents must actively reject when reviewing architecture, plans, code, or post-mortems. Used by architect (pre-impl), pm (planning), senior-dev (impl), l3-support (post-incident).
roslyn-query
Query .NET/C# codebases using Roslyn AST analysis via dotnet run file. Use for tracing data flow, auditing API usage, finding pattern violations, or ad-hoc codebase queries.
apex-review
Cross-cutting review of recent work — catches gaps between specialists. Use when asked to "review what we built", "check the work", "pre-launch review", or after completing a significant chunk of work.