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 frankchu91/mindbase-llm-wiki --skill mindbasegit clone --depth 1 https://github.com/frankchu91/mindbase-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/frankchu91/mindbase-llm-wiki/mindbase)<a href="https://agentmods.dev/skills/frankchu91/mindbase-llm-wiki/mindbase"><img src="https://agentmods.dev/badge/skills/frankchu91/mindbase-llm-wiki/mindbase/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/frankchu91/mindbase-llm-wiki/mindbase"><img src="https://agentmods.dev/badge/skills/frankchu91/mindbase-llm-wiki/mindbase.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 | $0.00105 | $0.01074 |
| Opus 5.5 | $0.00042 | $0.00430 |
| Sonnet 5.5 | $0.00021 | $0.00215 |
| Haiku 4.5 | $0.00011 | $0.00107 |
Grade A, and why
mindbase 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 1mo 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MindBase: Karpathy's LLM-Wiki Pattern (wiki v2 edition)
You operate as the maintainer of the user's per-project research wiki.
1 — Mission
Build and maintain a compounding knowledge base. The user feeds sources (papers, URLs, daily thoughts). You write structured markdown across README.md + context.md + sources/ so the wiki gets richer with every source.
This is NOT RAG — knowledge accumulates, doesn't get re-derived. Your job is the bookkeeping humans abandon: cross-references, summary updates, contradiction flagging, log keeping.
2 — Per-project layout (memorize this)
~/mindbase-data/projects/<project-id>/
├── README.md Operations manual — how this project works. User-editable.
├── context.md Curated truth, regenerated by /mb:build. LLM-owned.
├── index.yaml Auto-generated nav manifest. Never edit manually.
├── soul.md OPTIONAL — project identity/mission/voice.
├── sources/
│ ├── contributors/<user>/YYYY-MM-DD.md Append-only daily entries.
│ ├── research/<slug>.md /mb:research output.
│ └── raw/<date>/<id>.{md,meta.json,...} PDFs, web clips.
├── state/<agent>/... Agent-managed, opaque to /mb:build.
├── logs/YYYY-MM-DD.md Daily audit log.
└── artifacts/ Generated outputs.
Project location resolution (in order):
- Explicit
--project <id>in command args MINDBASE_PROJECT_IDenvironment variable~/mindbase-data/config.json→currentProjectId- If none → tell user to run
/mb:loador/mb:init
Every operation reads via mindbase MCP tools — never grep the wiki manually.
3 — The 4 Operations
3.1 INGEST/CONTRIBUTE — /mb:contribute <text-or-path-or-url>
Input scale calibrates the output:
- Short user thought (≲ 200 chars, time-anchored, first-person): 1-3 actions — append to today's contributor file + optional concept link. Routing keywords:
daily:,concept:,daily+concept:force route. - Substantive source (URL / PDF / long paste): full extraction, 5-15 actions touching context.md + sources/research/.
- Ambiguous middle: decide by content type. Decision/insight → capture scale. Multi-claim narrative → ingest scale.
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.
- 1mo ago First seen · 84 lines · 105 tokens per session scan A bbb6000d95b5
mindbase is a skill published in the GitHub repository frankchu91/mindbase-llm-wiki (135 stars, last pushed 7d ago), licensed MIT. It adds 105 tokens to every session and 1,074 once invoked, about $0.0004 per session on Opus 5.5. 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
llm-wiki
Build and maintain a persistent, interlinked Obsidian-compatible markdown wiki using Karpathy's LLM Wiki pattern. Extension-backed with auto-generated metadata, guardrails, and 14 custom tools (+3 opt-in agent-trajectory tools).
wiki-crystallize
Distil a chat thread, research session, or working document into a structured wiki page capturing the current state of knowledge. Always use this skill when the user says /wiki-crystallize, 'save this to my wiki', 'capture what we've worked out', 'write this up as a wiki page', 'update my wiki from this conversation'…
llm-wiki-maintain
Orchestrates the recurring daily-maintenance loop for the PM wiki — registry-driven multi-source sweep, ingest, daily brief, brief rotation, and a health check — with explicit interactive-vs-autonomous mode handling.
wiki-query
Answer a question using the compiled wiki knowledge base, synthesising a response with [[wikilink]] citations. Always use this skill when the user says /wiki-query, 'what does my wiki say about', 'what do I know about', 'check my notes on', 'search my wiki for', or 'what's the current state of [topic] in my notes'.…
wiki
A persistent Markdown knowledge base maintained by an AI agent. Markdown is a plain-text format for structured notes; the knowledge base can hold personal research or documentation about an open-source project's design.
wiki-daily
A daily workflow for a LoreKit knowledge collection that captures notes, tasks, programming decisions, and review material before compiling them into daily or longer-term summaries.