cog-braindump-capture

cog-braindump-capture is a skill for Claude Code from a5c-ai/babysitter. It costs 19 tokens per session (361 once invoked), scanned A, original, MIT.

A note-capture workflow that sorts raw thoughts into separate personal, professional, and project folders. It also records dates, topics, confidence, links, and references to related notes.

In plain words
What is it for?
Use it to process brain dumps, extract URLs, classify notes, add cross-references, and commit the captured entries to Git.
Why use it?
It keeps mixed, unstructured thoughts from being misplaced or lost. Separate folders help prevent personal and professional information from being combined.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

About the project

Babysitter is a workflow engine for AI coding agents that enforces predefined steps, quality checks, human approvals, and decision records. It is used to coordinate complex, repeatable agent workflows across supported coding tools. The catalogue contains skills, agents, instructions, settings, a plugin, and an MCP integration for its workflow.

a5c-ai/babysitter · 1,772 stars · on GitHub · a5c.ai

Install

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.

agentmods
npx agentmods add skills/a5c-ai/babysitter/braindump-capture
Any agent
npx skills add a5c-ai/babysitter --skill braindump-capture
Clone the repo
git clone --depth 1 https://github.com/a5c-ai/babysitter

Made for: Claude Code.

Wrote 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.

agentmods badge for cog-braindump-capture

README.md
[![agentmods](https://agentmods.dev/badge/skills/a5c-ai/babysitter/braindump-capture.svg)](https://agentmods.dev/skills/a5c-ai/babysitter/braindump-capture)
Your own site
<a href="https://agentmods.dev/skills/a5c-ai/babysitter/braindump-capture"><img src="https://agentmods.dev/badge/skills/a5c-ai/babysitter/braindump-capture.svg" alt="Measured on agentmods" height="20"></a>
Per session 19 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 361 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00019 $0.00361
Opus 5 $0.00010 $0.00180
Sonnet 5 $0.00004 $0.00072
Haiku 4.5 $0.00002 $0.00036

Measured 3d ago against content hash 04550c4a74ce, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

cog-braindump-capture 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 3d 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.

library/methodologies/cog-second-brain/skills/braindump-capture/SKILL.md · 43 lines

What it actually says

  • Classify content into personal, professional, and project-specific domains
  • Extract embedded URLs for separate processing
  • Route classified content to appropriate vault directories
  • Tag entries with metadata: date, domain, confidence, topics
  • Maintain strict domain separation (02-personal vs 03-professional)
  • Quality-gated capture with iterative refinement

Tool Use Instructions

  1. Use file-read to load user profile from 00-inbox for classification context
  2. Classify content by domain using natural language analysis
  3. Use file-write to create classified entries in appropriate vault directories
  4. Use file-search to find related existing entries for cross-referencing
  5. Use file-write to add cross-references to new and existing entries
  6. Use git-commit to commit captured content

Examples

{
  "vaultPath": "./cog-vault",
  "captureType": "braindump",
  "content": "Had a great idea about the auth system redesign. Also need to book vacation for July. The React 19 features look promising for our dashboard project.",
  "targetQuality": 80
}
Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 3d ago First seen · 43 lines · 19 tokens per session scan A 04550c4a74ce

Subscribe to this mod's changes

cog-braindump-capture is a skill published in the GitHub repository a5c-ai/babysitter (1,772 stars, last pushed today), licensed MIT. It adds 19 tokens to every session and 361 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 2026-09-03.

Related

Other skills, from other repositories