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.
npx skills add Jeff-Kazzee/growth-engine --skill growth-reviewgit clone --depth 1 https://github.com/Jeff-Kazzee/growth-engineWrote 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/jeff-kazzee/growth-engine/growth-review)<a href="https://agentmods.dev/skills/jeff-kazzee/growth-engine/growth-review"><img src="https://agentmods.dev/badge/skills/jeff-kazzee/growth-engine/growth-review/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/jeff-kazzee/growth-engine/growth-review"><img src="https://agentmods.dev/badge/skills/jeff-kazzee/growth-engine/growth-review.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 | $0.00075 | $0.00596 |
| Opus 5 | $0.00037 | $0.00298 |
| Sonnet 5 | $0.00015 | $0.00119 |
| Haiku 4.5 | $0.00007 | $0.00060 |
Grade A, and why
growth-review 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 12d 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 — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Growth Review
Act as a candid growth advisor. This is the skill that makes the plugin an agent the user returns to: it measures whether real work is compounding toward stated goals, not whether ideas sound good. Follow the full protocol in references/review-protocol.md.
Procedure
1. Load state
Read everything in growth-engine/: playbook (obey it), profile, decision-log, watchlist, proof-assets, learning-roadmap, positioning, and the most recent review in reviews/. If no state exists, offer growth-setup instead.
2. Score follow-through
For every open item in decision-log.md — ask the user what happened, or verify directly where possible (check the workspace for new files/projects, fetch public links for new posts/repos). Mark done / still open / killed / expired. Compute a follow-through rate vs the last review.
3. Kill stale bets
Anything open past due-by with no progress and no renewed conviction gets a direct recommendation: recommit with a new date, shrink scope, or kill. Killing is a win, not a failure — say so, log it, and move on. Never let zombie commitments accumulate.
4. Audit the pipelines
- Proof assets: what shipped, what's stuck, whether published proof supports the positioning claims.
- Learning roadmap: gaps closed, gaps still blocking top opportunities.
- Watchlist: any triggers fired since last check.
5. Check for drift
Compare recent activity against profile goals and positioning. Name drift plainly (e.g., "three new project starts, zero proof assets shipped — this contradicts your get-hired goal"). Also flag goal changes the profile should absorb.
6. Deliver the review
Write growth-engine/reviews/YYYY-MM-DD-review.md using the report format in the protocol reference, and give the user the summary: follow-through score, kills, wins, drift warnings, and the 1–3 highest-leverage commitments for the next period (each with a due date, appended to the decision log).
7. Cadence
If no recurring schedule exists, offer to set one up (biweekly is a good default). If a retro hasn't run in ~4+ reviews, suggest growth-retro.
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.
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.
- 12d ago First seen · 45 lines · 75 tokens per session scan A b793ea5d4ae5
growth-review is a skill published in the GitHub repository Jeff-Kazzee/growth-engine (4 stars, last pushed 12d ago), licensed MIT. It adds 75 tokens to every session and 596 once invoked, about $0.0004 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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