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 digital-stoic-org/agent-skills --skill troubleshootgit clone --depth 1 https://github.com/digital-stoic-org/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/digital-stoic-org/agent-skills/troubleshoot)<a href="https://agentmods.dev/skills/digital-stoic-org/agent-skills/troubleshoot"><img src="https://agentmods.dev/badge/skills/digital-stoic-org/agent-skills/troubleshoot/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/digital-stoic-org/agent-skills/troubleshoot"><img src="https://agentmods.dev/badge/skills/digital-stoic-org/agent-skills/troubleshoot.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 | $0.00043 | $0.00916 |
| Opus 5 | $0.00022 | $0.00458 |
| Sonnet 5 | $0.00009 | $0.00183 |
| Haiku 4.5 | $0.00004 | $0.00092 |
Grade A, and why
troubleshoot 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 11d 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 — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Troubleshoot
Search-first diagnostic workflow. Human executes commands.
⚠️ AskUserQuestion Guard
CRITICAL: After EVERY AskUserQuestion call, check if answers are empty/blank. Known Claude Code bug: outside Plan Mode, AskUserQuestion silently returns empty answers without showing UI.
If answers are empty: DO NOT proceed with assumptions. Instead:
- Output: "⚠️ Questions didn't display (known Claude Code bug outside Plan Mode)."
- Present the options as a numbered text list and ask user to reply with their choice number.
- WAIT for user reply before continuing.
Workflow
0.Load → 1.Search → 2.Qualify → 3.Diagnose → 4.Investigate → 5.Persist → 6.Learn
0. Load Learnings
Read $PRAXIS_DIR/reference/troubleshoot/learnings.yaml if exists. Apply known patterns before searching.
1. Search (do first)
80% of bugs solved online.
- WebSearch:
[error] [stack] [framework]on SO, GitHub, Docs, Reddit - Solution found → skip to 5.Learn
2. Qualify (2-3 questions)
AskUserQuestion:
- Stack? (language, framework, runtime)
- Environment? (local, container, cloud)
- Changed recently? (deploy, config, dependency)
3. Diagnose
See protocols/diagnose.md for details.
- Mental models: Check learnings.yaml → WebSearch pattern → reason with 5 Whys/Fishbone
- Isolation: Wolf Fence (binary search), swap one variable, minimal repro
- Root cause drill: 5 Whys, Fishbone 6 M's
Pattern matches → suggest fix, skip OODA
4. Investigate (OODA)
Only if diagnosis inconclusive.
- Observe: User runs command, pastes output
- Orient: Analyze, update hypothesis
- Decide: Next command or confirm cause
- Act: Suggest fix (user executes)
Exit when root cause confirmed and fix verified.
5. Persist Thinking Artifact ⚠️ MANDATORY
MUST execute after root cause confirmed and fix verified. DO NOT skip. DO NOT wait for user to ask.
Persist the diagnostic session to $PRAXIS_DIR/thinking/troubleshoot/{project}/{date}-{slug}-llm.md.
What ships with it
4 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.
- 11d ago First seen · 105 lines · 43 tokens per session scan A 1ce6d090f593
troubleshoot is a skill published in the GitHub repository digital-stoic-org/agent-skills (20 stars, last pushed 4d ago), licensed MIT. It adds 43 tokens to every session and 916 once invoked, about $0.0002 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 2026-08-30.
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