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 skills/siddsachar/row-bot/brain_dumpnpx skills add siddsachar/row-bot --skill brain_dumpgit clone --depth 1 https://github.com/siddsachar/row-botWrote 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/siddsachar/row-bot/brain_dump)<a href="https://agentmods.dev/skills/siddsachar/row-bot/brain_dump"><img src="https://agentmods.dev/badge/skills/siddsachar/row-bot/brain_dump.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 | $0.00017 | $0.00495 |
| Opus 5 | $0.00009 | $0.00247 |
| Sonnet 5 | $0.00003 | $0.00099 |
| Haiku 4.5 | $0.00002 | $0.00049 |
Grade A, and why
brain_dump 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
When the user says they want to brain dump, get thoughts out of their head, or starts listing a stream of unstructured ideas/worries/plans, follow these steps:
- Listen First — Let the user finish their dump. Don't interrupt or start processing until they signal they're done (or you detect a natural pause).
- Categorise — Sort everything they mentioned into buckets:
- 🎯 Action Items — Things that need doing
- 💡 Ideas — Things to explore later
- 🤔 Decisions — Things that need a decision
- 📝 Notes — Things to just remember
- Prioritise Actions — For the action items, suggest a priority order based on urgency and importance.
- Check Existing Knowledge — Before saving, check recalled memories and use
search_memoryfor key topics mentioned. If the user already brain-dumped about the same project or topic, update those existing memories instead of creating duplicates. - Save to Memory — Store action items, ideas, and notes to memory so nothing is lost. Use descriptive subjects like
Brain Dump — March 28 Actionsor topic-based subjects for easy retrieval. Link related items to existing entities (people, projects, events) in the knowledge graph. - Summarise — Present a clean overview of everything captured:
- How many items in each category
- What was saved to memory (new vs updated)
- What still needs a decision
Keep the tone supportive and non-judgmental. The point is to get everything out of the user's head and into a trusted system.
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 · 49 lines · 17 tokens per session scan A 6cd77076d1cb
brain_dump is a skill published in the GitHub repository siddsachar/row-bot (1,480 stars, last pushed 6d ago), licensed Apache-2.0. It adds 17 tokens to every session and 495 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.
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