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.
git 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/research)<a href="https://agentmods.dev/commands/frankchu91/mindbase-llm-wiki/research"><img src="https://agentmods.dev/badge/commands/frankchu91/mindbase-llm-wiki/research/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/commands/frankchu91/mindbase-llm-wiki/research"><img src="https://agentmods.dev/badge/commands/frankchu91/mindbase-llm-wiki/research.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00032 | $0.00335 |
| Opus 5.5 | $0.00013 | $0.00134 |
| Sonnet 5.5 | $0.00006 | $0.00067 |
| Haiku 4.5 | $0.00003 | $0.00034 |
Grade A, and why
research 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.
What it actually says
Deep research a topic for a MindBase project.
Arguments: $ARGUMENTS
Parse:
--project <id>or-p <id>flag → target project id. If omitted, usesconfig.jsoncurrentProjectId.- Remaining text = the topic. If empty, ask the user.
Dispatch the researcher sub-agent via the Task tool with subagent_type: "researcher" and prompt:
Research topic: ${topic}.
projectId: ${resolvedProjectId}
The researcher threads projectId through every MCP call (search_wiki, ask_wiki, research_save, append_log, validate_structure) and saves the output to ${resolvedProjectId}/sources/research/.
When the sub-agent returns, present its summary verbatim. Then offer:
- "Run /mb:build -p ${resolvedProjectId} to fold these findings into context.md?"
- "Save a follow-up question as a contributor note?" → use
/mb:contribute -p ${resolvedProjectId} ...
Note: -p does NOT change current project — research is saved to the specified project only.
Examples:
/mb:research "AI agent marketplace"→ current project/mb:research -p ai-agents "transformer attention mechanisms"→ ai-agents/mb:research --project insurance "flood risk models 2026"→ insurance
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 · 30 lines · 32 tokens per session scan A 16c11307482a
research is a command published in the GitHub repository frankchu91/mindbase-llm-wiki (135 stars, last pushed 11d ago), licensed MIT. It adds 32 tokens to every session and 335 once invoked, about $0.0001 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 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.