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/backnotprop/pstack/principle-fix-root-causesnpx skills add backnotprop/pstack --skill principle-fix-root-causesgit clone --depth 1 https://github.com/backnotprop/pstackWhat 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 | $0.00042 | $0.00294 |
| Opus 5 | $0.00021 | $0.00147 |
| Sonnet 5 | $0.00008 | $0.00059 |
| Haiku 4.5 | $0.00004 | $0.00029 |
Grade A, and why
principle-fix-root-causes scanned grade A with 0 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
4 near-identical copies found in the catalogue:
- principle-fix-root-causes — 95% identical, 2 lines differ
- principle-fix-root-causes — 95% identical, 2 lines differ
- principle-fix-root-causes — 94% identical, 4 lines differ
- principle-fix-root-causes — 92% identical, 3 lines differ
What it actually says
Fix Root Causes
When debugging, do not paper over symptoms. Trace every problem to its root cause and fix it there.
Why: Symptom fixes accumulate. Each workaround makes the system harder to reason about, and the real bug remains. Root-cause fixes are slower upfront but reduce total debugging time.
Pattern:
- Reproduce first (if you can't reproduce it, you can't verify your fix)
- Ask "why" until you hit the root cause
- Resist the urge to add guards (adding a nil check to silence a crash is a symptom fix)
- If a workaround needs a paragraph-long comment to justify it, the code is wrong (fix the code, not the comment)
- Check for the pattern, not just the instance (grep for the same pattern, fix all instances)
- When stuck, instrument. Don't guess (add logging, read the actual error)
Restart bugs: suspect state before code
Code doesn't change between runs. State does. When something "fails after restart," suspect stale persistent state first: config files, caches, lock files, serialized state. If clearing a state file restores behavior, prioritize state validation as the fix.
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 · 24 lines · 42 tokens per session scan A cfae13b5a3e2
principle-fix-root-causes is a skill published in the GitHub repository backnotprop/pstack (181 stars, last pushed 13d ago), licensed MIT. It adds 42 tokens to every session and 294 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. 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.
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…
agent-host-chat-contributions
Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.
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.