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 skills add anh-chu/llm-wiki-pm --skill llm-wiki-researchgit clone --depth 1 https://github.com/anh-chu/llm-wiki-pmWrote 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/anh-chu/llm-wiki-pm/llm-wiki-research)<a href="https://agentmods.dev/skills/anh-chu/llm-wiki-pm/llm-wiki-research"><img src="https://agentmods.dev/badge/skills/anh-chu/llm-wiki-pm/llm-wiki-research/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/anh-chu/llm-wiki-pm/llm-wiki-research"><img src="https://agentmods.dev/badge/skills/anh-chu/llm-wiki-pm/llm-wiki-research.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00042 | $0.02116 |
| Opus 5 | $0.00021 | $0.01058 |
| Sonnet 5 | $0.00008 | $0.00423 |
| Haiku 4.5 | $0.00004 | $0.00212 |
Grade A, and why
llm-wiki-research 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 11d 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 — 256 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LLM Wiki Research
Sub-skill of llm-wiki-pm. Handles research sprints, competitive deep dives, and auto-enrichment of stub entities. Delegates all URL fetching to worker-source-fetcher so privacy filtering and raw/ logging happen correctly.
WebFetch note: WebFetch is listed in allowed-tools for quick page previews (e.g., confirming a URL before delegation). For source capture (saving to raw/), always delegate to worker-source-fetcher. Never call WebFetch directly for source saving — privacy filtering and raw/ logging won't happen.
Orient First
Orient per AGENTS.md before any writes:
- Read
$WIKI/SCHEMA.md - Read
$WIKI/index.md - Read last 20-30 lines of
$WIKI/log.md - Read
$WIKI/overview.md
Research sprints may create many pages. Get user confirmation before creating 5+ pages.
Wiki Path Resolution
WIKI=$(cat .wiki-path 2>/dev/null | tr -d '[:space:]')
WIKI=${WIKI:-${CLAUDE_PLUGIN_OPTION_wiki_path:-${WIKI_PATH:-$(pwd)}}}
Worker Delegation
This skill uses worker-source-fetcher for all URL fetching. Never call WebFetch directly for source capture — always invoke the worker:
"Use worker-source-fetcher to fetch [URL]"
This ensures privacy filtering and raw/ logging happen correctly. The worker returns:
"OK: saved to raw/<subdir>/<slug>.md" — use that path for synthesis.
Operation 1: Research Sprint
Trigger: "research sprint on [topic]", "deep research on [topic]"
① Define scope
Confirm with user:
- What is the topic / question to answer?
- Target depth: surface / standard / deep
- Time budget (number of sources)
② Wiki-first
grep -r "<topic>" $WIKI --include="*.md" -l
Read all relevant pages. Surface: "Wiki has N relevant pages. Here's what we already know: [...]. Gaps: [...]."
③ Research plan
Present 3-5 specific sources to fetch — name each, why it's relevant, what question it answers. Typical: analyst reports, company pages, recent press, whitepapers, industry forums. Get user confirmation before fetching.
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.
- 11d ago First seen · 256 lines · 42 tokens per session scan A cef2cc6d13f7
llm-wiki-research is a skill published in the GitHub repository anh-chu/llm-wiki-pm (6 stars, last pushed 1mo ago), licensed MIT. It adds 42 tokens to every session and 2,116 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 2026-08-31.
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