debug-my-harness
Diagnose why an agent harness misbehaved by reading the local flight-recorder ledger (.vigiles/runs.jsonl) — which skills fired or got hijacked, which hooks blocked or wrongly allowed, which subagent tool-contract violations happened, and how a skill's trigger rate moved. Use when asked why a skill stopped firing, why a hook didn't block, why the wrong skill ran, or to debug/investigate what the harness actually did. NOT for writing new rules (use strengthen) or editing the spec (use edit-spec).
Works with
---
name: debug-my-harness
description: Diagnose why an agent harness misbehaved by reading the local flight-recorder ledger (.vigiles/runs.jsonl) — which skills fired or got hijacked, which hooks blocked or wrongly allowed, which subagent tool-contract violations happened, and how a skill's trigger rate moved. Use when asked why a skill stopped firing, why a hook didn't block, why the wrong skill ran, or to debug/investigate what the harness actually did. NOT for writing new rules (use strengthen) or editing the spec (use edit-spec).
license: MIT
---
Diagnose harness misbehavior from the **flight recorder** — the local, append-only ledger
at `.vigiles/runs.jsonl` that vigiles writes as your harness runs. It records what actually
happened, so you debug from evidence instead of guessing.
## What's in the ledger
One JSON record per line, each with a `kind`:
- `hook` — a compiled-hook gate decision: `{event, decision: allow|deny|ask, mode: enforce|observe, rule, cmd, reason}`.
- `agent` — a subagent tool-contract decision: `{name, tool, allowed, reason}` (a `false` = the agent went outside its lane).
- `skill` — a skill activation: `{name, fired}`.
- `eval` — a measured metric: `{name, metric, value}` (e.g. trigger-rate recall/precision).
- `capability-diff` — a blast-radius change: `{pr, added, removed, widened}`.
## Instructions
### Step 1: Read the ledger
Read `.vigiles/runs.jsonl` (JSONL — one record per line; tolerate a torn last line). If it's
absent or empty, say so — there's nothing recorded yet; suggest running the harness (or
`vigiles audit`) first. Do NOT fabricate records.
### Step 2: Answer the specific question, evidence-first
Match the user's question to the ledger:
- **"Why did skill X stop firing / why does the wrong one run?"** — count `skill` fires by
name over time. If X's fire-rate dropped, look for a sibling that fired on the same kinds
of prompts (a **selection collision**) and check their descriptions for overlap. Recommend
differentiating or merging the descriptions.
- **"Why didn't my hook block that?"** — find `hook` records for the event. A `decision:
allow` on something that should be denied, or `mode: observe` (shadow, never blocks), or
the absence of any record, tells you which. Recommend flipping `observe`→`enforce` or
fixing the gate logic.
- **"Did a subagent misbehave?"** — list `agent` records with `allowed: false`: the agent
reached for a tool outside its declared contract. Point at the contract to tighten or widen.
- **"Is it getting worse?"** — compare `eval` metric values (recall/precision) across runs;
a downward trend is drift (often after a harness/model upgrade).
### Step 3: Recommend a fix, tied to the evidence
Prefer **promoting an ignored-but-decidable rule from prose to a deterministic gate**: a
repeated `agent` violation or a rule the agent keeps breaking → a compiled hook or a tighter
tool-contract (the `strengthen` skill can help). A description collision → differentiate the
skill descriptions. Always cite the specific records you based the diagnosis on.
### Step 4: Offer the next step
If the fix is a spec change, hand off to `edit-spec`. If it's promoting guidance to a linter
rule, hand off to `strengthen`. If a behavioral claim needs measuring (does the skill fire
now?), hand off to `test-harness` (`measureTriggerRate`).More Debugging skills
diagnosing-bugs
mattpocock/skills
Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.
explore-code
lllllllama/rigorpilot-skills
Rigor Improve implementation leaf skill for auditable candidate implementation in deep learning research repositories. Use when the researcher explicitly authorizes exploratory work on an isolated branch or worktree to transplant modules, adapt a backbone, add LoRA or adapter layers, replace a head, or stitch together meaningful low-risk migration ideas with rollback-aware records in `explore_outputs/`. Do not use for end-to-end exploration orchestration on top of `current_research`, trusted baseline reproduction, conservative debugging, environment setup, verified contribution claims, or default repository analysis.
safe-debug
lllllllama/rigorpilot-skills
Rigor Debug / Rigor Audit skill for deep learning research work. Use when the user pastes a traceback, terminal error, CUDA OOM, checkpoint load failure, shape mismatch, NaN loss symptom, or training failure and wants conservative diagnosis before any patching, with debug fixes clearly separated from research contributions. Do not use for broad refactoring, speculative adaptation, automatic exploratory patching, or general repository familiarization.

