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/patrick-fu/awesome-skills/log-driven-debuggingnpx skills add patrick-fu/awesome-skills --skill log-driven-debugginggit clone --depth 1 https://github.com/patrick-fu/awesome-skillsWhat 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 | $0.00037 | $0.01056 |
| Opus 5 | $0.00018 | $0.00528 |
| Sonnet 5 | $0.00007 | $0.00211 |
| Haiku 4.5 | $0.00004 | $0.00106 |
Grade A, and why
log-driven-debugging 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 3d 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 — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When the bug is slippery, stop guessing and build observability.
This skill is for situations where:
- the visible symptom is known, but the actual failure layer is not
- static code reading is no longer enough
- one execution with good logs can collapse a large search space
The workflow is simple:
- decide where to instrument
- add high-signal logs
- have the user rerun the scenario
- analyze the returned logs
- only then propose or implement the real fix
First move
Before adding any logs, ask the user for a log prefix.
This is required, not optional. Explain why briefly: the prefix makes the new logs searchable and prevents them from being lost in normal application output.
Good prefixes look like:
PatrickMyDebugDebugTrace
Prefer a short prefix that:
- is unique in the current codebase
- is easy to grep
- is unlikely to collide with existing production logs
If the user does not care, ask for one and wait. Do not silently invent a prefix unless the user explicitly delegates that choice.
Logging strategy
Do not scatter random prints everywhere. Instrument the execution path deliberately.
Choose logs around:
- entry points where the user action first enters the system
- state transitions where data changes shape
- serialization or conversion boundaries
- async handoff points
- final outbound effects such as send, save, render, request, or callback
For each log, include enough structure to reconstruct the flow:
- the shared prefix
- a timestamp
- a short tag for the subsystem or phase
- the minimum fields needed to compare expected vs actual behavior
Treat the timestamp as part of the standard format, not a nice-to-have. For tricky bugs, ordering is often as important as values.
Prefer logs that answer:
- Did this code path run?
- In what order did the steps happen?
- What data existed at this point?
- Where did duplication, loss, mutation, or branching first appear?
Avoid:
- giant object dumps unless they are truly needed
- vague messages like "here" or "called"
- logging so much that the signal disappears
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.
- 3d ago First seen · 157 lines · 37 tokens per session scan A 8307cb2f1d64
log-driven-debugging is a skill published in the GitHub repository patrick-fu/awesome-skills (57 stars, last pushed today), licensed MIT. It adds 37 tokens to every session and 1,056 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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