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/jbdamask/mcbrain/local-research-dbnpx skills add jbdamask/McBrain --skill local-research-dbgit clone --depth 1 https://github.com/jbdamask/McBrainWrote 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/jbdamask/mcbrain/local-research-db)<a href="https://agentmods.dev/skills/jbdamask/mcbrain/local-research-db"><img src="https://agentmods.dev/badge/skills/jbdamask/mcbrain/local-research-db.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 | $0.00086 | $0.02694 |
| Opus 5 | $0.00043 | $0.01347 |
| Sonnet 5 | $0.00017 | $0.00539 |
| Haiku 4.5 | $0.00009 | $0.00269 |
Grade A, and why
local-research-db 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.
How it starts
The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Local Research DB
Initialize (or extend) a local research-task tracker for a McBrain vault. The tracker is a single JSONL file at <vault>/raw/research_tasks/tasks.jsonl — one JSON object per line, all topics in one file, topic-as-a-field (not a folder). The companion skill local-research-runner drains "To do" rows from this file, runs research subagents, writes findings to raw/notes/, and flips rows to "Done".
When to Use
- User says "set up a local research tracker", "register a research topic in my vault", "spin up a JSONL backlog for X".
- User has run
mcbrain-setupand choseLocalas the research-tracker backend, and now wants to add an additional topic.
Prerequisites
- The vault must be a McBrain vault — registered in
~/.mcbrain/registry.jsonand visible via the mcbrain MCP'slist_vaultstool. The skill writes into the vault at its absolute path from the registry. - Python 3 must be available on the user's host (used by
local-research-runner, not by this skill — but worth surfacing so the user knows the runner will work). - No external installations, no extra MCP connectors, no tokens.
Inputs to Collect
- Research topic — free-form string (e.g. "CRISPR base editing", "AI evals literature"). Used to derive the topic slug and to label tracker rows. If the user did not supply one, ask.
- Associated McBrain vault — see Identifying the McBrain vault below. Resolve this before writing anything.
That's the entire input set. There is no parent page, no database name, no schema choice.
Identifying the McBrain vault
McBrain vaults are registered in ~/.mcbrain/registry.json ({"vaults": [{"name", "path", "created"}]}). To pick the right one:
- List the registered vaults. In Claude Desktop / Cowork, call the mcbrain MCP's
list_vaultstool. In Claude Code, read~/.mcbrain/registry.jsondirectly. - Zero matches. No vault is registered. Tell the user the tracker can't be set up because there is no vault to write into. Stop.
- One match. Use it. Mention the choice in your confirmation message ("I'll register this tracker with
mcbrain-ai-science.") so the user can correct you if it's wrong. - Multiple matches. Try to infer from the research topic by simple substring/keyword overlap with the vault names — e.g. topic "AI evals literature" →
mcbrain-ai-scienceis a much better match thanmcbrain-finance. Only auto-pick when one candidate is an obvious winner; otherwise ask:
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 · 149 lines · 86 tokens per session scan A 16313d2882d3
local-research-db is a skill published in the GitHub repository jbdamask/McBrain (2 stars, last pushed 2mo ago), licensed MIT. It adds 86 tokens to every session and 2,694 once invoked, about $0.0004 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 2026-08-31.
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