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/exportgit 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/export)<a href="https://agentmods.dev/commands/frankchu91/mindbase-llm-wiki/export"><img src="https://agentmods.dev/badge/commands/frankchu91/mindbase-llm-wiki/export.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 | $0.00023 | $0.00240 |
| Opus 5 | $0.00012 | $0.00120 |
| Sonnet 5 | $0.00005 | $0.00048 |
| Haiku 4.5 | $0.00002 | $0.00024 |
Grade A, and why
export 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.
What it actually says
Export a MindBase project.
Arguments: $ARGUMENTS
Parse:
--project <id>or-p <id>flag → target project id. If omitted, usesconfig.jsoncurrentProjectId.- First non-flag positional = target format (
markdown-bundledefault, orzip-archive).
Call mindbase_export({ projectId, target }). Report the output path.
Note: -p does NOT change current project — export operates on the specified project only.
Useful for:
- Sharing a project snapshot with a collaborator
- Importing into a different MindBase install
- Archiving completed projects
Examples:
/mb:export→ current project, markdown-bundle/mb:export zip-archive→ current, zip/mb:export -p ai-agents→ ai-agents, markdown-bundle/mb:export -p ai-agents zip-archive→ ai-agents, zip
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 First seen · 27 lines · 23 tokens per session scan A 820ea0c79a7a
export is a command published in the GitHub repository frankchu91/mindbase-llm-wiki (93 stars, last pushed 10d ago), licensed MIT. It adds 23 tokens to every session and 240 once invoked, about $0.0001 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-run
Run the full wiki cycle: discover → ingest → lint. Optionally schedule for auto-updates.