trace
Execution-path mapping for entry points, data flow, side effects, and blast radius before risky work.
Works with
--- name: trace description: Execution-path mapping for entry points, data flow, side effects, and blast radius before risky work. license: MIT --- # Trace ## Purpose Use `$trace` before a risky edit or review when you need to know what code path actually runs, what it touches, and what could break downstream. ## Workflow 1. Find the entry points. 2. Follow data flow through the changed or targeted path. 3. Map side effects: - storage writes - network calls - UI state changes - background work 4. Identify risky branches and missing guards. 5. Name the concrete files the next pass should touch. ## Suggested Tools - `omx explore search` - `omx explore symbols` - `omx explore refs` - `omx explore diff` ## Output Standard - entry points - downstream side effects - risky branches - likely blast radius - recommended edit boundary
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.
