cog-weekly-reflection

cog-weekly-reflection is a skill for Claude Code, Codex from a5c-ai/babysitter. It costs 20 tokens per session (343 once invoked), scanned A, original, MIT.

A weekly reflection workflow that looks for patterns across personal life, professional development, and project progress.

In plain words
What is it for?
Use it to analyse daily, personal, professional, and project entries, then write a weekly check-in with cross-domain insights and actionable observations.
Why use it?
It removes the need to review many separate notes and guess how they connect. It helps reveal relationships between energy, skills, productivity, blockers, and project results.

Skill for Claude CodeCodex

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 · 1,769 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/weekly-reflection
Any agent
npx skills add a5c-ai/babysitter --skill weekly-reflection
Clone the repo
git clone --depth 1 https://github.com/a5c-ai/babysitter

Made for: Claude Code, Codex.

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-weekly-reflection

README.md
[![agentmods](https://agentmods.dev/badge/skills/a5c-ai/babysitter/weekly-reflection.svg)](https://agentmods.dev/skills/a5c-ai/babysitter/weekly-reflection)
Your own site
<a href="https://agentmods.dev/skills/a5c-ai/babysitter/weekly-reflection"><img src="https://agentmods.dev/badge/skills/a5c-ai/babysitter/weekly-reflection.svg" alt="Measured on agentmods" height="20"></a>
Per session 20 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 343 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 $0.00020 $0.00343
Opus 5 $0.00010 $0.00171
Sonnet 5 $0.00004 $0.00069
Haiku 4.5 $0.00002 $0.00034

Measured 2d ago against content hash 1adfec130f66, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

cog-weekly-reflection 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 2d 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/weekly-reflection/SKILL.md · 45 lines

What it actually says

  • Identify patterns in personal domain (energy, mood, productivity)
  • Identify patterns in professional domain (skills, career, industry)
  • Identify patterns in project domain (velocity, blockers, progress)
  • Synthesize cross-domain connections
  • Generate actionable insights with confidence levels
  • Quality-gated reflection with iterative refinement

Tool Use Instructions

  1. Use file-read to load entries from 01-daily, 02-personal, 03-professional, 04-projects
  2. Use file-search to find related entries across sections
  3. Analyze patterns within each domain independently
  4. Synthesize cross-domain connections
  5. Use file-write to create weekly check-in in 01-daily
  6. Add cross-references to identified patterns
  7. Use git-commit to commit reflection

Examples

{
  "vaultPath": "./cog-vault",
  "mode": "weekly-checkin",
  "userName": "Alex",
  "rolePack": "engineer",
  "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. 2d ago First seen · 45 lines · 20 tokens per session scan A 1adfec130f66

Subscribe to this mod's changes

cog-weekly-reflection is a skill published in the GitHub repository a5c-ai/babysitter (1,769 stars, last pushed yesterday), licensed MIT. It adds 20 tokens to every session and 343 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.