cog-onboarding

cog-onboarding is a skill for Claude Code from a5c-ai/babysitter. It costs 19 tokens per session (366 once invoked), scanned A, original, MIT.

A setup workflow for creating a personal knowledge vault and tailoring it to a role such as engineering, product management, design, or marketing.

In plain words
What is it for?
Use it to initialise a vault, choose a role-based workflow, record interests and news sources, and configure connections to tools such as GitHub, Linear, Slack, and PostHog.
Why use it?
It removes the repetitive work of building folders, profiles, templates, Git tracking, and privacy settings by hand.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it to initialise a vault, choose a role-based workflow, record interests and news sources, and configure connections to tools such as GitHub, Linear, Slack, and PostHog.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/a5c-ai/babysitter/onboarding
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 · 1,777 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.

Any agent
npx skills add a5c-ai/babysitter --skill onboarding
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-onboarding

README.md
[![agentmods](https://agentmods.dev/badge/skills/a5c-ai/babysitter/onboarding.svg)](https://agentmods.dev/skills/a5c-ai/babysitter/onboarding)
Your own site
<a href="https://agentmods.dev/skills/a5c-ai/babysitter/onboarding"><img src="https://agentmods.dev/badge/skills/a5c-ai/babysitter/onboarding.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 366 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00366
Opus 5 $0.00010 $0.00183
Sonnet 5 $0.00004 $0.00073
Haiku 4.5 $0.00002 $0.00037

Measured 4d ago against content hash b150c294887e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

cog-onboarding 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.

library/methodologies/cog-second-brain/skills/onboarding/SKILL.md · 45 lines

What it actually says

  • Configure one of 7 role packs: Product Manager, Engineering Lead, Engineer, Designer, Founder, Marketer, Custom
  • Set up user profile with interests, domains, and news sources
  • Configure external integrations (GitHub, Linear, Slack, PostHog)
  • Create personalized workflow templates based on role
  • Initialize Git tracking for the vault

Tool Use Instructions

  1. Use file-read to check for existing vault at the specified path
  2. Use directory-create to build the COG directory structure
  3. Use file-write to create profile.md in 00-inbox with role pack configuration
  4. Use git-init to initialize Git repository in the vault
  5. Use file-write to create .gitignore with privacy-sensitive patterns
  6. Use git-commit to commit initial vault structure

Examples

{
  "userName": "Alex",
  "rolePack": "engineer",
  "vaultPath": "./cog-vault",
  "integrations": {
    "github": { "org": "my-org", "repos": ["main-repo"] }
  }
}
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. 4d ago First seen · 45 lines · 19 tokens per session scan A b150c294887e

Subscribe to this mod's changes

cog-onboarding is a skill published in the GitHub repository a5c-ai/babysitter (1,777 stars, last pushed 2d ago), licensed MIT. It adds 19 tokens to every session and 366 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.