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 commands/frankchu91/mindbase-llm-wiki/lintgit 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/commands/frankchu91/mindbase-llm-wiki/lint)<a href="https://agentmods.dev/commands/frankchu91/mindbase-llm-wiki/lint"><img src="https://agentmods.dev/badge/commands/frankchu91/mindbase-llm-wiki/lint.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 5.1 | $0.00037 | $0.00332 |
| Opus 5 | $0.00018 | $0.00166 |
| Sonnet 5 | $0.00007 | $0.00066 |
| Haiku 4.5 | $0.00004 | $0.00033 |
Grade A, and why
lint 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 6d 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
Health-check a MindBase project.
Arguments: $ARGUMENTS
Parse in order:
--project <id>or-p <id>flag → target project id.- First positional arg (if not a flag) → target project id (fallback).
- If neither present → uses
config.jsoncurrentProjectId.
Dispatch the curator sub-agent via the Task tool with subagent_type: "curator" and prompt:
Run wiki health check for project ${resolvedProjectId}.
The curator threads projectId through every MCP call (validate_structure, run_wiki_health, find_orphans, find_contradictions, find_gaps, suggest_links, append_log).
When the sub-agent returns, present its findings verbatim to the user (the formatting is already done).
Offer one of:
- "Want me to file a follow-up note for any of these?" → if yes, call
/mb:contribute -p ${resolvedProjectId}for the chosen finding (preserve the same project). - "Rebuild context to refresh stale data?" → if yes, dispatch builder with the same
projectId.
Note: -p / positional does NOT change current project.
Examples:
/mb:lint→ current project/mb:lint -p ai-agents→ lint ai-agents (current unchanged)
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.
- 6d ago First seen · 31 lines · 37 tokens per session scan A 57936c4bafe2
lint is a command published in the GitHub repository frankchu91/mindbase-llm-wiki (95 stars, last pushed 12d ago), licensed MIT. It adds 37 tokens to every session and 332 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 commands, from other repositories
wiki-query
Ask questions against the wiki. Synthesizes answers from wiki pages with cross-reference citations.
wiki-req
Capture and decompose a concept into atomic, traceable wiki requirements. Clarifies ambiguous requirements, splits them into atomic pieces, and persists them as wiki/requirements/ pages with status tracking.
wiki-ingest
Process new source packets and synthesize them into wiki knowledge pages.
wiki-record
Capture the just-completed task's tool-call trajectory into the wiki as agent working-memory, then optionally distill it into a reusable skill.
wiki-retro
Save an atomic insight from the current task into the wiki. Creates a single markdown file that layered recall surfaces in future sessions.
wiki-discover
Auto-discover new sources from the web. Searches based on config topics and known knowledge gaps.