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 agentmods add skills/sandsower/beislid/debugnpx skills add sandsower/beislid --skill debuggit clone --depth 1 https://github.com/sandsower/beislidWhat 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 | $0.00026 | $0.00398 |
| Opus 5 | $0.00013 | $0.00199 |
| Sonnet 5 | $0.00005 | $0.00080 |
| Haiku 4.5 | $0.00003 | $0.00040 |
Grade A, and why
debug 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 2d 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.
What it actually says
Debug Method
Find the root cause before touching code. No quick fixes, no guessing, no shotgun debugging.
Phases
1. Reproduce
- Read the error message carefully — the full stack trace, not just the last line
- Reproduce the failure consistently
- If you can't reproduce it, you don't understand it yet
2. Investigate
- Check recent changes (
git log,git diff) that could have introduced the issue - Find a working reference — when did this last work? What's different?
- Trace the data flow from input to error point
- In multi-component systems, isolate which component fails first
3. Hypothesize
- Form a single hypothesis based on evidence gathered
- Test it minimally — the smallest change that proves or disproves the hypothesis
- If disproved, go back to step 2 with new information
- If you're stuck after 3 hypotheses, say "I don't understand this yet" and surface to the user
4. Fix
- Write a failing test that captures the bug
- Implement the fix — one change at a time
- Verify the test goes from red to green
- Run the full suite to check for regressions
Red Flags
Stop yourself if you're thinking:
- "Let me just try changing X" — that's guessing
- "Quick fix for now" — that's deferring understanding
- "Multiple changes at once" — that's making it harder to know what worked
- "I don't fully understand but this should work" — go back to investigate
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.
- 2d ago First seen · 46 lines · 26 tokens per session scan A 16a2a1dfa459
debug is a skill published in the GitHub repository sandsower/beislid (10 stars, last pushed 2d ago), licensed MIT. It adds 26 tokens to every session and 398 once invoked, about $0.0001 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.
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