Borrowing it
Nothing to install: this file belongs to Pratiyush/llm-wiki. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Pratiyush/llm-wiki/master/.claude/skills/llmwiki-ingest/SKILL.mdgit clone --depth 1 https://github.com/Pratiyush/llm-wikiWrote 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/pratiyush/llm-wiki/llmwiki-ingest)<a href="https://agentmods.dev/skills/pratiyush/llm-wiki/llmwiki-ingest"><img src="https://agentmods.dev/badge/skills/pratiyush/llm-wiki/llmwiki-ingest/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/pratiyush/llm-wiki/llmwiki-ingest"><img src="https://agentmods.dev/badge/skills/pratiyush/llm-wiki/llmwiki-ingest.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00083 | $0.00712 |
| Opus 5 | $0.00042 | $0.00356 |
| Sonnet 5 | $0.00017 | $0.00142 |
| Haiku 4.5 | $0.00008 | $0.00071 |
Grade A, and why
llmwiki-ingest 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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
llmwiki-ingest
What this skill does
Takes a source file (or a folder) and turns it into wiki pages following the Karpathy LLM Wiki pattern:
- Writes a
wiki/sources/<slug>.mdsummary - Creates/updates entity pages for people, companies, projects, tools, libraries mentioned
- Creates/updates concept pages for ideas, patterns, decisions discussed
- Cross-links everything with
[[wikilinks]] - Flags contradictions
- Updates
wiki/index.md,wiki/overview.md,wiki/log.md
When to use
- User says "ingest this file", "add this to the wiki", "process this into the wiki"
- User runs the
/wiki-ingestslash command - User says "sync the wiki" — in that case, the
llmwiki-syncskill runs the converter first, then invokes this skill for each new file
Workflow
Follow the Ingest Workflow from the repo's CLAUDE.md exactly:
- Read the source file(s) with the Read tool
- Read
wiki/index.mdandwiki/overview.mdfor context - Write
wiki/sources/<slug>.mdusing the Source Page Format - Update
wiki/index.md— new entry under## Sources - Update
wiki/overview.mdif substantial new info - Create/update entity pages (
wiki/entities/<TitleCase>.md) - Create/update concept pages (
wiki/concepts/<TitleCase>.md) - Cross-link with
[[wikilinks]]under## Connections - Flag contradictions under
## Contradictions - Append to
wiki/log.md:## [YYYY-MM-DD] ingest | <title>
Session-specific rules
When the source is under raw/sessions/ (a session transcript converted by the converter):
- Trust the frontmatter as authoritative (project, started, model, tools_used, etc.)
- Do not copy the
## Conversationsection verbatim — use it as raw material to summarise - Create a project entity page at
wiki/entities/<ProjectSlug>.mdwith a## Sessionslist - Extract decisions into
wiki/concepts/— anything the user explicitly locked - Extract tools used — every entry in
tools_usedis a candidate entity - If
is_subagent: true— link to the parent session rather than creating a new project entity
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 · 57 lines · 83 tokens per session scan A 94c31909a264
llmwiki-ingest is a skill published in the GitHub repository Pratiyush/llm-wiki (387 stars, last pushed 2mo ago), licensed MIT. It adds 83 tokens to every session and 712 once invoked, about $0.0004 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
release-governance
Use when preparing, auditing, releasing, PDF-hardening, or rebuttal-hardening academic manuscripts, datasets, artifacts, reviewer packets, or claim registers involving multiple refs, local assets, human labels, agent-assisted drafts, wide tables, figure provenance, submission PDFs, or evidence-boundary checks.
read
Read PDF page by page with structured output — key arguments, terms glossary, thesis connections. Use when reading academic papers, books, or articles.
markitdown
A Python utility for converting various file formats (PDF, Word, Excel, PowerPoint, etc.) to Markdown. Use this skill to install and use MarkItDown for document conversion.
Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and…
nature-figure
Create, revise, audit, and export submission-grade scientific figures for Nature-family and other high-impact venues in Python (matplotlib/seaborn) or R (ggplot2/patchwork/ComplexHeatmap), including multi-panel plots, figures4papers-style work, and journal-ready SVG/PDF/TIFF outputs. Use for paper or scientific plots…
nature-paper2ppt
A workflow for turning a scientific paper, preprint, PDF, or reading notes into a Chinese PowerPoint presentation in a Nature-style format. It is intended for talks such as journal clubs, lab meetings, seminars, conferences, and thesis defences.