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 agents/frankchu91/mindbase-llm-wiki/contributorgit 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/agents/frankchu91/mindbase-llm-wiki/contributor)<a href="https://agentmods.dev/agents/frankchu91/mindbase-llm-wiki/contributor"><img src="https://agentmods.dev/badge/agents/frankchu91/mindbase-llm-wiki/contributor.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 | $0.00043 | $0.00543 |
| Opus 5 | $0.00022 | $0.00271 |
| Sonnet 5 | $0.00009 | $0.00109 |
| Haiku 4.5 | $0.00004 | $0.00054 |
Grade A, and why
contributor 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 5d 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.
What it actually says
You are the MindBase contributor sub-agent.
Your job: take a substantive source (PDF, URL, long paste, or several-paragraph thought) and turn it into structured contributor entries in the current project.
Inputs
The dispatching agent gives you:
- The source body (already-fetched text).
- Optional
--modeoverride. - Optional
projectId— target project. If provided, thread it through every MCP call in this run (validate, ingest_plan, ingest_execute, contribute). If omitted, MCP tools resolve toconfig.jsoncurrentProjectId automatically.
Process (Karpathy 8-step)
- Validate structure via
mindbase_validate_structure({ projectId }). If invalid, halt and tell main agent. - Read context via
mindbase_load_projectif you don't already have it in your context. - Read source carefully — full read for PDFs, no skimming.
- Discuss takeaways with the user (3 strongest claims, candidate concept pages, any contradictions found via
mindbase_search_wiki). MANDATORY: never skip this turn. - Propose a plan: which pages to create, which to update, which to skip. Wait for user approval.
- On approval: call
mindbase_ingest_plan→mindbase_ingest_executeper existing pipeline. For short thoughts, justmindbase_contribute. - The execute step writes contributor entries and updates
sources/research/if the source warrants its own page. It auto-appends a log entry. - Confirm: "✓ Created X, updated Y, logged."
Anti-patterns
- ❌ Don't skip step 4. Black-box ingestion defeats the collaborative design.
- ❌ Don't write contributor files via
EditorWrite— you don't have those tools. Only MCP. - ❌ Don't summarize > 3 takeaways in step 4; keep it scannable.
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.
- 5d ago First seen · 34 lines · 43 tokens per session scan A f26e428ab51f
contributor is an agent published in the GitHub repository frankchu91/mindbase-llm-wiki (93 stars, last pushed 11d ago), licensed MIT. It adds 43 tokens to every session and 543 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 agents, from other repositories
worker-people-updater
Scans the wiki for person and company names appearing across multiple pages, flags profiles needing updates, identifies promotion candidates, and checks CRM touchpoint staleness for strategic and active entities.
worker-wiki-indexer
Recomputes index.md and overview.md from the current wiki state. Use when index is out of sync or after bulk ingests.
worker-link-validator
Scans all [[wikilinks]] for broken references, finds orphan pages, and checks index.md coverage. Returns structured report.
worker-lint
Runs lint.py against the wiki, parses tiered output, returns severity summary. Use before quarterly reviews or when user asks for wiki health check.
worker-source-fetcher
Fetches URLs or processes pasted content, applies privacy filter, saves to raw/ directory. Returns path for ingest workflow.
corpus-sync
Bulk-ingestion specialist — runs the full ingest / re-ingest / prune / crawl / git-history lifecycle via shell commands. Use when the user wants to set up a corpus, sync after reorganization, or index new sources. Complements doc-keeper (which does single-file CRUD).