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/lifedever/skills-plugin/debug-modenpx skills add lifedever/skills-plugin --skill debug-modegit clone --depth 1 https://github.com/lifedever/skills-pluginWhat 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 | $0.00104 | $0.03672 |
| Opus 5 | $0.00052 | $0.01836 |
| Sonnet 5 | $0.00021 | $0.00734 |
| Haiku 4.5 | $0.00010 | $0.00367 |
Grade C, and why
debug-mode scanned grade C with 2 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 2d 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
rm -rf .claude-debug/ Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s http://localhost:3333/health How it starts
The opening of the file, as written. The whole thing — 356 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debug Mode — Runtime Debugging
Locate and fix bugs by inserting log probes, collecting runtime data, and analyzing execution traces. Multi-language support.
⛔ MANDATORY RULES — ENFORCED VIA CHECKPOINTS
This skill uses a checkpoint system. You MUST print each checkpoint marker BEFORE proceeding to the next step. If you skip a checkpoint, the entire debug session is invalid.
Each step ends with a checkpoint that you must print exactly:
✅ CHECKPOINT 1: Probe plan created — N probes planned✅ CHECKPOINT 2: Log collector started✅ CHECKPOINT 3: N probes inserted into source files(you must have used the Edit tool N times)✅ CHECKPOINT 4: N log entries collected✅ CHECKPOINT 5: Root cause identified with log evidence✅ CHECKPOINT 6: Fix applied and verified with probes✅ CHECKPOINT 7: All probes removed, cleanup complete
HARD RULES:
- You CANNOT print CHECKPOINT 5 without first printing CHECKPOINTS 1-4
- You CANNOT propose a fix without citing specific log entries as evidence
- You MUST use the Edit tool to physically insert probe code into source files at Step 3 — reading code and proposing probes mentally does not count
- You MUST collect and read actual log output at Step 5 — you cannot analyze logs you haven't collected
- Static analysis may reveal an obvious issue — you may fix it first. But if the fix doesn't work, you MUST instrument and collect runtime data before attempting another fix. The purpose is runtime verification, not guesswork.
Core Principles
- Understand before instrumenting — Read code and error messages, identify suspect areas, place probes only on critical paths
- Minimal intrusion — Probes must not alter original logic, only observe and record
- Closed loop — Instrument → Run → Collect → Analyze → Fix → Verify → Clean up
Workflow
Step 0: Triage — Gather Context from User
Before reading any code, ask the user targeted questions to collect clues. Only ask what you don't already know — skip questions the user has already answered in their initial message.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 356 lines · 104 tokens per session scan C 65663a41e2dc
debug-mode is a skill published in the GitHub repository lifedever/skills-plugin (11 stars, last pushed 11d ago), licensed MIT. It adds 104 tokens to every session and 3,672 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it C with 2 findings (recursive force delete, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…