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 praneybehl/llm-wiki-plugin --skill llm-wikigit clone --depth 1 https://github.com/praneybehl/llm-wiki-pluginWrote 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/praneybehl/llm-wiki-plugin/llm-wiki)<a href="https://agentmods.dev/skills/praneybehl/llm-wiki-plugin/llm-wiki"><img src="https://agentmods.dev/badge/skills/praneybehl/llm-wiki-plugin/llm-wiki.svg" alt="Measured on agentmods" 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 | $0.00221 | $0.04614 |
| Opus 5 | $0.00111 | $0.02307 |
| Sonnet 5 | $0.00044 | $0.00923 |
| Haiku 4.5 | $0.00022 | $0.00461 |
Grade A, and why
llm-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 — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LLM Wiki
A skill for building and maintaining an LLM-curated knowledge base at any user-chosen filesystem location, following the pattern Andrej Karpathy described in his April 2026 gist. One personal wiki can compound knowledge across projects, or a wiki can be isolated inside one project. The user curates sources and asks questions; the LLM does the bookkeeping.
The pattern in one paragraph
Conventional RAG re-derives knowledge from raw chunks on every query; nothing accumulates. The LLM Wiki pattern flips this: when a new source arrives, the LLM compiles it once into a persistent, structured wiki — extracting concepts, writing entity pages, updating cross-references, flagging contradictions. Subsequent queries read the pre-synthesized wiki rather than the raw sources. Knowledge compounds. The user is in charge of sourcing and asking good questions; the LLM handles the summarizing, linking, and consistency work that humans abandon wikis over.
When to use this skill
The trigger surface is broad. Any time the user is accumulating textual material over time — research papers, articles, transcripts, meeting notes, book chapters, customer calls, code repos, journal entries — and would benefit from having that material organized rather than dumped into a chat each session, this skill applies. It is equally useful for one source ("ingest this paper") and for the steady-state operations against an existing wiki ("what does my wiki say about diffusion models", "lint the wiki", "what's missing").
Resolve the wiki before doing anything else. Prefer, in order: a path named by the user, a path in the nearest project instructions, a path in global agent instructions, then wiki/ in the current project. Read the resolved wiki's SCHEMA.md; it may override defaults documented here. Never silently combine two wikis. If no wiki exists, run the bootstrap step below.
All relative wiki/ and raw/ paths in this skill refer to the resolved wiki and raw-source roots, not necessarily the current working directory.
What ships with it
26 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/graph_gitignore.template 27 B
- assets/graph_README.md.template 2.0 KB
- assets/index.md.template 775 B
- assets/log.md.template 499 B
- assets/ontology.yaml.template 3.2 KB
- assets/page.md.template 805 B
- assets/SCHEMA.md.template 6.0 KB
- assets/wiki-cache_gitignore.template 14 B
- references/agent-memory-integration.md 6.0 KB
- references/architecture.md 9.6 KB
- references/graph-workflow.md 7.1 KB
- references/ingest-workflow.md 9.5 KB
- references/lint-workflow.md 7.1 KB
- references/page-conventions.md 5.8 KB
- references/query-workflow.md 7.5 KB
- references/retrieval-setup.md 4.1 KB
- references/scaling-playbook.md 6.8 KB
- scripts/init_wiki.py 9.1 KB runs code
- scripts/setup_wiki.py 2.5 KB runs code
- scripts/test_link_resolution.py 6.2 KB runs code
- scripts/wiki_graph_extract.py 21 KB runs code
- scripts/wiki_graph_lint.py 16 KB runs code
- scripts/wiki_graph_query.py 9.3 KB runs code
- scripts/wiki_lint.py 15 KB runs code
- scripts/wiki_search.py 32 KB runs code
- scripts/wiki_stats.py 5.9 KB runs code
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 Changed · +15 lines 177aa3a54120
- 8d ago First seen · 165 lines · 221 tokens per session scan A 58d65db5577a
llm-wiki is a skill published in the GitHub repository praneybehl/llm-wiki-plugin (100 stars, last pushed 4d ago), licensed MIT. It adds 221 tokens to every session and 4,614 once invoked, about $0.0011 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.
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