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/root-causenpx skills add lifedever/skills-plugin --skill root-causegit 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 | $0.00156 | $0.01023 |
| Opus 5 | $0.00078 | $0.00511 |
| Sonnet 5 | $0.00031 | $0.00205 |
| Haiku 4.5 | $0.00016 | $0.00102 |
Grade A, and why
root-cause 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 3d 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.
How it starts
The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Root Cause — First-Principles Analysis
Force reasoning from fundamental facts. No analogies, no "this looks like X so do Y", no pattern-matching from similar codebases. Start from what is actually true and derive what should be done.
When to Use
- Debugging: The surface fix is obvious, but you suspect a deeper issue
- Architecture: Deciding between approaches — is the familiar pattern actually right for this case?
- Solution design: Before adopting an existing pattern, verify it's the right one
The Process
Step 1: Strip Away Assumptions
List every assumption baked into the current approach or the proposed fix. For each one, ask: is this actually true in our specific context, or are we just carrying it over from convention?
Print each assumption as:
⚠️ Assumption: [what we're taking for granted]
Evidence for: [does evidence support this?]
Evidence against: [anything contradicting it?]
Verdict: ✅ Holds / ❌ Doesn't hold / ❓ Unverified
Step 2: Identify Fundamental Facts
List only what is provably true — from the code, the data, the logs, the runtime behavior. No "usually", no "typically", no "in most projects".
📌 Fact 1: [concrete observation with file:line or log evidence]
📌 Fact 2: [concrete observation with file:line or log evidence]
...
Step 3: Derive the Answer from Facts
From the facts alone, reason forward:
- For bugs: what is the actual causal chain from trigger to symptom?
- For architecture: what does the data flow / responsibility boundary / actual constraint demand?
- For design: what solution follows from the real requirements, not from "how we did it last time"?
Step 4: Compare with the Obvious Answer
Now compare your first-principles derivation with whatever the "obvious" or "conventional" answer was:
🔍 Conventional approach: [what pattern-matching would suggest]
🔍 First-principles answer: [what the facts demand]
🔍 Delta: [where they differ and why it matters]
If they agree — great, the conventional approach is validated. If they diverge — the delta is where the real insight lives.
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.
- 3d ago First seen · 88 lines · 156 tokens per session scan A 229bf0f6cc8e
root-cause is a skill published in the GitHub repository lifedever/skills-plugin (11 stars, last pushed 11d ago), licensed MIT. It adds 156 tokens to every session and 1,023 once invoked, about $0.0008 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
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brainstorming
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auto-perf-optimize
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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
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