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/encod3d-sec/torch/wikinpx skills add Encod3d-Sec/TORCH --skill wikigit clone --depth 1 https://github.com/Encod3d-Sec/TORCHWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/encod3d-sec/torch/wiki)<a href="https://agentmods.dev/skills/encod3d-sec/torch/wiki"><img src="https://agentmods.dev/badge/skills/encod3d-sec/torch/wiki.svg" alt="Measured on agentmods" height="20"></a>What 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 | $0.00031 | $0.01185 |
| Opus 5 | $0.00015 | $0.00593 |
| Sonnet 5 | $0.00006 | $0.00237 |
| Haiku 4.5 | $0.00003 | $0.00119 |
Grade A, and why
wiki scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Wiki Search and Maintenance
qmd is a CLI + MCP server that provides semantic and keyword search over wiki/. The MCP server (wiki-search) exposes two tools consumed by Claude Code directly. The CLI is used for maintenance (re-index, status).
All paths are relative to the vault root ($QMD_VAULT).
Prerequisites
QMD_VAULT must point to your vault root (no trailing slash). Export it in your shell profile:
export QMD_VAULT="/path/to/your/ObsidianVaults/ClaudeBrain"
If a new session does not inherit it, prefix commands with QMD_VAULT=... qmd ... or source your profile. qmd is installed as a bun global (bun install -g @qmd/cli); if the qmd command is not found, ensure ~/.bun/bin is on PATH.
Searching via MCP (preferred in-session path)
When the wiki-search MCP is active, prefer these tools over the CLI - they avoid the 3-4 second model load on every invocation:
| Tool | Purpose |
|---|---|
mcp__wiki-search__qmd_query |
Semantic (vector) search - use for concepts, techniques, intent |
mcp__wiki-search__qmd_search |
Keyword (substring) search - use for exact strings, tool names, CVE IDs |
CLAUDE.md rule: never read wiki/index.md to find pages - always search first.
Searching via CLI
Use when MCP is unavailable or for one-off maintenance.
Semantic query (5 results, default):
qmd query "CDN bypass origin IP"
Semantic query (custom result count):
qmd query -n 10 "JWT empty secret"
Keyword search:
qmd keyword "pnpm"
Output format: [score] path/relative/to/wiki/ followed by a chunk of the matching content.
Maintenance
Re-index after adding or editing pages (run once after a bulk write, not per file):
qmd update
Expected output: Indexing wiki... Done. N chunks indexed.
The CUDA warning about an old driver is harmless - the model runs on CPU.
Check index size:
qmd status
Output: Collection: wiki Chunks: N
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.
- 4d ago First seen · 139 lines · 31 tokens per session scan A 2ddebeb6ba6c
wiki is a skill published in the GitHub repository Encod3d-Sec/TORCH (284 stars, last pushed 3d ago), licensed MIT. It adds 31 tokens to every session and 1,185 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.
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…