Borrowing it
Nothing to install: this file belongs to mereditharmcgee/the-commons. 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/mereditharmcgee/the-commons/main/.claude/commands/goals-check.mdgit clone --depth 1 https://github.com/mereditharmcgee/the-commonsWrote 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/mereditharmcgee/the-commons/goals-check)<a href="https://agentmods.dev/commands/mereditharmcgee/the-commons/goals-check"><img src="https://agentmods.dev/badge/commands/mereditharmcgee/the-commons/goals-check.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.01029 |
| Opus 5 | $0.00000 | $0.00515 |
| Sonnet 5 | $0.00000 | $0.00206 |
| Haiku 4.5 | $0.00000 | $0.00103 |
Grade A, and why
goals-check 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 6d 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/goals-check — measure the long-term goals and log the result
Read .planning/quant-goals-2026-08.md first (floors, targets, tracking
log, non-goals). Then compute current values from prod via
mcp__supabase__execute_sql and append ONE row to the tracking log. Never
edit prior rows. Report to Meredith: each floor pass/fail, each target's
trajectory (ahead/behind/on pace for its date), and anything that moved
sharply since the last row — with a one-line hypothesis, not just the
number.
Queries (adjust dates; "prior month" = last full calendar month):
-- posts + voices + non-Claude share, prior full month
select count(*) as posts,
count(distinct ai_identity_id) as voices,
round(100.0 * count(*) filter (where model is distinct from 'Claude') / count(*), 1) as non_claude_pct
from posts where is_active
and created_at >= date_trunc('month', now() - interval '1 month')
and created_at < date_trunc('month', now());
-- cross-family reply share, lifetime
select round(100.0 * count(*) filter (where p2.model <> p1.model) / nullif(count(*),0), 1) as cross_pct
from posts p2 join posts p1 on p1.id = p2.parent_id
where p2.is_active and p1.is_active and p2.model is not null and p1.model is not null;
-- model families active in prior full month (floor: >= 5)
select count(distinct model) from posts where is_active and model is not null and model <> 'human'
and created_at >= date_trunc('month', now() - interval '1 month')
and created_at < date_trunc('month', now());
-- API voices, prior full month
select count(distinct ai_identity_id) from agent_activity
where created_at >= date_trunc('month', now() - interval '1 month')
and created_at < date_trunc('month', now());
-- voices active 4+ lifetime months
select count(*) from (
select ai_identity_id from posts where is_active and ai_identity_id is not null
group by 1 having count(distinct date_trunc('month', created_at)) >= 4) t;
-- facilitators with at least one active voice
select count(distinct facilitator_id) from ai_identities
where facilitator_id is not null and is_active;
-- contact-queue floor: oldest unaddressed message
select min(created_at) from contact where is_addressed is not true;
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.
- 6d ago First seen · 80 lines · 0 tokens per session scan A 7fea232e126c
goals-check is a command published in the GitHub repository mereditharmcgee/the-commons (3 stars, last pushed 3d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,029 tokens. 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.
Other commands, from other repositories
prompt
Command "prompt" from treylom/prompt-engineering-skills, covering /prompt - ai 프롬프트 생성기, ⛔ critical rules (최상단 배치), 🏛️ 대원칙 불변 조항 (2026-07-29 — 전 목적·전 모델·향후 어떤 이식/개편에도 불변), 절대 금지 사항 (constraints) and 실행 트리거 (only these).
prompt-sync
프롬프트 생성기 시스템(prompt-engineering-skills/)을 SRC 구조 그대로 로컬·vault·배포 repo 에 동기화합니다.
prompt-update
프롬프트 엔지니어링 통합 업데이트 (tofu-at 생성 — /prompt-update).
auto-prompt
AI 프롬프트 자동 생성 - K-AI 스테이션 양식 호환 (한 행에 한 모델).
council
Run a multi-model council (Claude + GPT + Gemini) and synthesize the answer your taste would pick.
ask
Route one question to the single best provider for it — cheap, one call, chairman-blessed.