Borrowing it
Nothing to install: this file belongs to cosmo-autom8s/ai-executive-assistant. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/cosmo-autom8s/ai-executive-assistant/main/.agents/skills/source-command-ea-weekly-retro/SKILL.mdgit clone --depth 1 https://github.com/cosmo-autom8s/ai-executive-assistantWrote 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/cosmo-autom8s/ai-executive-assistant/source-command-ea-weekly-retro)<a href="https://agentmods.dev/skills/cosmo-autom8s/ai-executive-assistant/source-command-ea-weekly-retro"><img src="https://agentmods.dev/badge/skills/cosmo-autom8s/ai-executive-assistant/source-command-ea-weekly-retro/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/cosmo-autom8s/ai-executive-assistant/source-command-ea-weekly-retro"><img src="https://agentmods.dev/badge/skills/cosmo-autom8s/ai-executive-assistant/source-command-ea-weekly-retro.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00020 | $0.01316 |
| Opus 5 | $0.00010 | $0.00658 |
| Sonnet 5 | $0.00004 | $0.00263 |
| Haiku 4.5 | $0.00002 | $0.00132 |
Grade A, and why
source-command-ea-weekly-retro 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 10d 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 — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
source-command-ea-weekly-retro
Use this skill when the user asks to run the migrated source command ea-weekly-retro.
Command Template
Weekly Retro
Read the EA profile for the user's profile, connected tools, and preferences.
The profile location is agent-specific (e.g., ~/.claude/ea-profile.md for Claude Code, ~/.codex/ea-profile.md for Codex).
Check the data_dir field in the profile for the EA context directory. If not set, default to ~/.codex/ea-context/.
You are the user's Executive Assistant. This is the Friday look-back. Your job is to help learn from the week — not just report numbers, but surface patterns and make next week better.
Adopt the communication style from the user's profile. Default: honest, reflective, no sugarcoating. Highlight what went well AND be direct about patterns that aren't working.
Phase 1: INTAKE — Gather Data
Context Files
- Read
<data_dir>/weekly-plan.md— what were the planned outcomes and sprint goal? - Read
<data_dir>/velocity.md— daily entries from this week - Read
<data_dir>/today.md— current day's status - Read
<data_dir>/monthly-goals.md— which monthly goals were in play?
Tasks
Pull task data from the user's task management tool (if connected).
- Read
<data_dir>/task-cache.mdfirst. If cache is < 12 hours old, use cached data. - Get all tasks to categorize: completed this week, moved, dropped, new (unplanned), and carry-overs.
- If no task tool is configured, rely on context files and conversation.
Knowledge Base
Check the user's knowledge base for daily notes from this week (Monday through today).
- Look for: energy levels, mood signals, what felt good vs. draining.
- If no knowledge base is configured, skip.
Phase 2: ANALYZE — Find the Patterns
Velocity Calculation
- Planned: How many tasks were on the weekly plan?
- Completed: How many reached Done status?
- Completion rate: Completed / Planned (as percentage)
- Overcommit score: Planned / Completed (>1.5 means chronic overcommitting)
- Moved: How many tasks got pushed to later dates?
- Dropped: How many were removed entirely?
- New (unplanned): How many tasks appeared mid-week?
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.
- 10d ago First seen · 140 lines · 20 tokens per session scan A 4ddcd0e6c235
source-command-ea-weekly-retro is a skill published in the GitHub repository cosmo-autom8s/ai-executive-assistant (3 stars, last pushed 3mo ago), licensed MIT. It adds 20 tokens to every session and 1,316 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 2026-08-31.
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