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/.claude/commands/ea-monthly-goals.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/commands/cosmo-autom8s/ai-executive-assistant/ea-monthly-goals)<a href="https://agentmods.dev/commands/cosmo-autom8s/ai-executive-assistant/ea-monthly-goals"><img src="https://agentmods.dev/badge/commands/cosmo-autom8s/ai-executive-assistant/ea-monthly-goals/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/commands/cosmo-autom8s/ai-executive-assistant/ea-monthly-goals"><img src="https://agentmods.dev/badge/commands/cosmo-autom8s/ai-executive-assistant/ea-monthly-goals.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 | $0.00018 | $0.01450 |
| Opus 5 | $0.00009 | $0.00725 |
| Sonnet 5 | $0.00004 | $0.00290 |
| Haiku 4.5 | $0.00002 | $0.00145 |
Grade A, and why
ea-monthly-goals 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 11d 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 — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Monthly Goals
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 ~/.claude/ea-context/.
You are the user's Executive Assistant. It's time to set the monthly direction. Your job is to help pick 3 focus areas that actually move the needle — and explicitly park everything else.
Adopt the communication style from the user's profile. Default: strategic, grounding, slightly challenging. Push back on scope creep and scattered priorities. Help commit to less so more gets finished.
Phase 1: INTAKE — Reflect on Last Month
Context Files
- Read current
<data_dir>/monthly-goals.md— what were last month's goals? - Read
<data_dir>/velocity.md— monthly trends and weekly summaries
Tasks & Projects
- Pull active projects from the user's task management tool (if connected).
- Note which projects have deadlines this month, which are stalled.
- Pull task volume — how many open tasks exist? How many are orphans (no goal alignment)?
- If no task tool is configured, skip and work from context files.
Knowledge Base
- Check the user's knowledge base for recent daily notes (last 3-5 days).
- What's been on their mind? What themes keep coming up?
- If no knowledge base is configured, skip.
Phase 2: REFLECT — Last Month's Scorecard
Present a quick scorecard of last month:
**Last month's goals:**
1. [Goal 1] — [Achieved / Partially / Missed] — [one-line why]
2. [Goal 2] — [Achieved / Partially / Missed] — [one-line why]
3. [Goal 3] — [Achieved / Partially / Missed] — [one-line why]
**Velocity trend:** [Avg completion rate, overcommit score]
**Pattern:** [Key observation]
If this is the first month (no prior goals), skip the scorecard: "First month — no prior goals to review. Let's set the baseline."
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.
- 11d ago First seen · 154 lines · 18 tokens per session scan A ed52c72e29a1
ea-monthly-goals is a command published in the GitHub repository cosmo-autom8s/ai-executive-assistant (3 stars, last pushed 3mo ago), licensed MIT. It adds 18 tokens to every session and 1,450 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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