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 stark-ai-de/agent-skills --skill debugging-diagnosisgit clone --depth 1 https://github.com/stark-ai-de/agent-skillsWrote 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/stark-ai-de/agent-skills/debugging-diagnosis)<a href="https://agentmods.dev/skills/stark-ai-de/agent-skills/debugging-diagnosis"><img src="https://agentmods.dev/badge/skills/stark-ai-de/agent-skills/debugging-diagnosis/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/stark-ai-de/agent-skills/debugging-diagnosis"><img src="https://agentmods.dev/badge/skills/stark-ai-de/agent-skills/debugging-diagnosis.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 | $0.00053 | $0.00664 |
| Opus 5 | $0.00026 | $0.00332 |
| Sonnet 5 | $0.00011 | $0.00133 |
| Haiku 4.5 | $0.00005 | $0.00066 |
Grade A, and why
debugging-diagnosis 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 9d 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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debugging Diagnosis
Goal
Find the smallest proven cause of a bug, fix it, and leave regression coverage or clear validation evidence.
When to use
- The user reports a bug, failing test, runtime error, broken workflow, or flaky behavior.
- A prior fix was speculative and needs a reproducible diagnosis.
- The task needs root cause analysis before a code change.
When not to use
- The user asks for a pure design plan with no failing behavior.
- The task is a known mechanical edit with an obvious validation command.
- The user asks for a broad repo audit rather than a specific failure.
Inputs to inspect
- Exact error text, logs, screenshots, failing test output, or reproduction steps.
- Recent diffs and
git status --short. - Relevant package scripts, test commands, CI workflow, issue context, and domain docs if present.
- Existing tests around the failing behavior.
Workflow
- Establish the failure in the current environment or state what cannot be reproduced.
- Minimize the reproduction to the smallest command, input, route, component, or test case.
- Form one or more falsifiable hypotheses and inspect only the files needed to test them.
- Add temporary instrumentation only when it answers a specific question; remove it before completion.
- Fix the smallest cause that explains the reproduction.
- Add or update regression coverage at the observable behavior boundary.
- Re-run the reproduction and the smallest relevant validation command.
Safety rules
- Do not make broad rewrites before proving the failure path.
- Do not hide a failure by weakening assertions, swallowing errors, or deleting coverage.
- Do not leave debug logs, probes, or temporary scripts behind.
- Do not claim a bug is fixed without a passing reproduction or an explicit validation limitation.
References
No bundled references. If the repo has docs/agents/validation.md or domain docs, inspect them when selecting validation commands or domain-specific expected behavior.
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.
- 9d ago First seen · 85 lines · 53 tokens per session scan A 48199455672a
debugging-diagnosis is a skill published in the GitHub repository stark-ai-de/agent-skills (5 stars, last pushed yesterday), licensed Apache-2.0. It adds 53 tokens to every session and 664 once invoked, about $0.0003 per session on Opus 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
bug-fixing
Fix defects in the Composio SDK repository with focused reproduction, root-cause analysis, regression tests, and narrow verification. Use when the user reports a bug, failing test, CI regression, runtime defect, or incorrect SDK behavior. Do not use for new feature design or broad refactors.
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.
python-testing
Select and run Python SDK verification with nox, Makefile targets, Ruff, mypy, pytest markers, sanity tests, type inference checks, and build checks. Use when adding Python tests, diagnosing Python CI, or validating Python SDK/provider changes. Do not use for TypeScript-only checks.
typescript-testing
Select and run TypeScript SDK verification for packages, examples, type checks, linting, builds, Vitest suites, and runtime E2E tests. Use when adding tests, diagnosing TypeScript CI, choosing a focused test command, or validating TypeScript package changes. Do not use for Python-only checks.
potpie-debug-memory
Use while debugging or troubleshooting failures, flaky tests, incidents, production alerts, CI failures, local dev setup issues, repeated bugs, prior fixes, failed attempts, and verification history.
openlore-debug
Debug with OpenLore structural context, an explicit root-cause hypothesis, and RED/GREEN verification. Use when a bug, failure, or regression needs diagnosis and repair.