log-driven-diagnosis
Skill6 starsChanged 4 months agoApache-2.0View on GitHub
Use when debugging complex runtime failures, distributed systems, or issues where a local debugger cannot be attached.
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The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 3 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 8
When you cannot step through code, logs are your only visibility.
- Very specific: line 23
Time-bound the search: Never dump the whole log file — always grep for timestamps around the reported incident, or use tail:
- Distinctive: line 31
Identify the request ID: If the system uses distributed tracing or request IDs, find the ID associated with the error, then search the log …
- Distinctive: line 46
Add missing logs: If the logs do not provide enough visibility, your first action must be to *add temporary logging* to the application, …
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Purpose
When you cannot step through code, logs are your only visibility. Be methodical about extracting signal from noise — never dump whole log files into context.
When to Use
- Runtime failures where a debugger cannot be attached
- Distributed systems where the failure spans services
- Issues reproducible only from log evidence
Inputs
- Log files or a log explorer covering the incident window
- The incident timestamp and, if available, a request/trace ID
Workflow
Time-bound the search. Never dump the whole log file — always
grepfor timestamps around the reported incident, or usetail:tail -n 200 app.log # most recent context grep -n "2026-06-06T14:0" app.log # window around the incident awk '/14:02:00/,/14:05:00/' app.log # bounded slice between timestampsIdentify the request ID. If the system uses distributed tracing or request IDs, find the ID associated with the error, then search the log corpus for only that ID to trace the complete lifecycle of the failed request:
grep -n "ERROR" app.log | head -5 # find the failing entry and its ID grep -n "<request-id>" app.log # full lifecycle of that request # structured (JSON) logs: jq -c 'select(.request_id == "<request-id>")' app.log.jsonLook for preceding warnings. The
ERRORlog is usually just the final crash. The actual root cause is often aWARNINGor unexpectedINFOlog that occurred milliseconds earlier (e.g., a connection retry failing, or an empty array being returned):grep -n -B 20 "<error-text>" app.log | grep -inE "warn|retry|timeout|empty"- Add missing logs. If the logs do not provide enough visibility, your first action must be to add temporary logging to the application, reproduce the bug, and gather the new signals. Do not guess blindly if the logs are insufficient.
Output
- The traced lifecycle of the failing request
- The suspected root-cause log line(s), including any preceding warnings
- Any temporary logging added (flagged for later removal)
Verification
- Every search was time-bounded or ID-bounded — no full-file dumps in context
- Full request lifecycle traced when an ID exists
- Lines preceding the error inspected, not just the error line itself
- Temporary logging added (and flagged for removal) where visibility was missing
Failure Modes
- Error-line tunnel vision — reading only the final ERROR while the cause sits in an earlier WARNING.
- Context flooding — dumping megabytes of log into the conversation instead of bounded slices.
- Blind guessing — iterating on fixes when the honest move is adding logging and reproducing once more.
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