Borrowing it
Nothing to install: this file belongs to stevesolun/ctx. 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/stevesolun/ctx/main/.agents/skills/diagnosing-bugs/SKILL.mdgit clone --depth 1 https://github.com/stevesolun/ctxWrote 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/stevesolun/ctx/diagnosing-bugs)<a href="https://agentmods.dev/skills/stevesolun/ctx/diagnosing-bugs"><img src="https://agentmods.dev/badge/skills/stevesolun/ctx/diagnosing-bugs/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/stevesolun/ctx/diagnosing-bugs"><img src="https://agentmods.dev/badge/skills/stevesolun/ctx/diagnosing-bugs.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 | $0.00043 | $0.00450 |
| Opus 5.5 | $0.00017 | $0.00180 |
| Sonnet 5.5 | $0.00009 | $0.00090 |
| Haiku 4.5 | $0.00004 | $0.00045 |
Grade A, and why
diagnosing-bugs 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 1mo 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 — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Diagnosing Bugs
Start from evidence and adapt the depth of the investigation to the problem. Read relevant repository context and architectural decisions when they exist.
Establish a useful signal
Reproduce the reported symptom with the cheapest signal that distinguishes broken from fixed. A focused test or script is ideal when practical; logs, traces, snapshots, comparisons, or measured timings may be better for other failures. Tighten the loop by improving speed, specificity, and determinism.
If an exact reproduction is unavailable, continue with the strongest evidence available and state the limitation. Request an artifact, access, or temporary instrumentation only when it would materially improve the diagnosis.
For feedback-loop options and debugging tactics, load the
debugging playbook as needed. For a rare
manual reproduction, adapt
scripts/hitl-loop.template.sh.
Narrow and explain
Minimize the reproducing scenario when doing so will shrink the search space. Form a small ranked set of falsifiable hypotheses from the evidence, then choose probes that best distinguish them. Share hypotheses with the user when their domain knowledge could redirect the investigation; do not make routine progress depend on a checkpoint.
Use targeted instrumentation at boundaries that separate plausible causes. Change as little as practical per probe. For performance regressions, establish a baseline and use profiling, query plans, or bisection before optimizing.
Fix and verify
Add a regression test when a stable seam can represent the real failure. If it cannot, explain the coverage gap rather than adding a misleading test. Apply the smallest justified fix, then rerun both the focused signal and relevant nearby checks.
Remove temporary instrumentation and artifacts unless the user wants to retain them. Report the observed cause, the evidence that supports it, what was verified, and any remaining uncertainty. Recommend architectural follow-up only when the diagnosis exposes a concrete recurring weakness.
What ships with it
3 files 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.
- 1mo ago First seen · 50 lines · 43 tokens per session scan A 7006edd95cfb
diagnosing-bugs is a skill published in the GitHub repository stevesolun/ctx (589 stars, last pushed 11d ago), licensed MIT. It adds 43 tokens to every session and 450 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 2026-08-30.
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self-improve
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manage-skills
A maintenance workflow for checking whether project verification skills still cover the code and rules that changed during a session.