---

name: debug-mode description: Run an iterative, hypothesis-driven “debug mode” loop to diagnose and fix a bug using targeted instrumentation and log capture. Use when the user wants an interactive debug loop, when you need to quickly narrow a failure via added debug statements, or when you need a lightweight way to centralize logs from a repro run (via agent-skills debug server + SSE UI).

Debug Mode

Run a tight debug loop: form a hypothesis, instrument the smallest surface area, capture evidence, update the hypothesis, and repeat until you can ship a fix with a regression test (or a clear root-cause explanation).

This skill assumes you can add temporary debug statements and that you can ask the user to run a repro while a local log capture server is running.

Quick start

1. Start the log capture server:

Copyagent-skills debug

1. Ask the user to reproduce while sending logs to the server (pick a method):

• agent-skills debug send …
• curl -X POST … /v1/logs

1. Use the captured evidence to pick the next instrumentation point and repeat.

Reference: skills/debug-mode/references/debug-server.md.

Workflow (debug loop)

1. Establish the repro and success criteria.

   • Ask for exact commands/inputs and the expected vs actual outcome.
   • Freeze variables: versions, env, config, dataset, feature flags.
   • If the bug is flaky, ask for frequency and a “best repro” loop.

2. Form a falsifiable hypothesis.

   • Phrase it as: “If X is happening, we should observe Y at location Z.”
   • Prefer hypotheses that narrow the search space (not “something is wrong”).

3. Instrument minimally.

   • Add logs at decision boundaries, not every line.
   • Log identifiers and invariants (IDs, counts, state machine states), not entire blobs.
   • Include correlation keys (requestId, userId, jobId, etc.).

4. Capture and review evidence.

   • Use the debug server UI and/or the NDJSON file as the shared artifact.
   • Summarize the evidence in a small table: observation → supports/refutes → next step.

5. Iterate until root cause is isolated.

   • Move instrumentation “upstream” or “downstream” based on what you learned.
   • Delete/undo misleading logs; keep only the ones that pay rent.

6. Fix + lock it in.

   • Implement the smallest safe fix.
   • Add a regression test or a runnable repro script.
   • Remove or downgrade temporary debug statements.

Notes for using agent-skills debug

• Default auth is a random token printed at startup.
• By default, events are appended as NDJSON to .agent-skills/debug.ndjson (disable with --out=).
• Use headers for ingestion where possible; use ?token= mainly for the browser UI.
• Prefer structured JSON logs with stable keys over freeform text.