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 konglong87/superPM --skill analyze-growthgit clone --depth 1 https://github.com/konglong87/superPMWrote 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/konglong87/superpm/analyze-growth)<a href="https://agentmods.dev/skills/konglong87/superpm/analyze-growth"><img src="https://agentmods.dev/badge/skills/konglong87/superpm/analyze-growth/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/konglong87/superpm/analyze-growth"><img src="https://agentmods.dev/badge/skills/konglong87/superpm/analyze-growth.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00042 | $0.00486 |
| Opus 5 | $0.00021 | $0.00243 |
| Sonnet 5 | $0.00008 | $0.00097 |
| Haiku 4.5 | $0.00004 | $0.00049 |
Grade A, and why
analyze-growth 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 9d 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.
What it actually says
Overview
This command chains 4 skills into a complete growth analysis workflow:
- pm-aarrr — AARRR funnel analysis
- pm-report — Data report & user feedback
- pm-growth — Growth strategy & execution plan
- pm-iteration — Iteration planning
Each step pauses for user confirmation before proceeding.
Execution Flow
Step 1: AARRR Analysis
📈 Starting Step 1/4: AARRR Analysis This will analyze your growth funnel across Acquisition, Activation, Retention, Revenue, and Referral.
执行 /pm-aarrr
完成后，使用 AskUserQuestion 确认。
Step 2: Data Report
📈 Starting Step 2/4: Data Report This will generate a comprehensive data report with user feedback analysis.
执行 /pm-report
完成后，使用 AskUserQuestion 确认。
Step 3: Growth Strategy
📈 Starting Step 3/4: Growth Strategy This will develop a growth execution plan based on data insights.
执行 /pm-growth
完成后，使用 AskUserQuestion 确认。
Step 4: Iteration Planning
📈 Starting Step 4/4: Iteration Planning This will create an iteration plan with prioritized growth initiatives.
执行 /pm-iteration
Completion
✅ Growth analysis complete!
Generated documents:
- docs/03-增长迭代/AARRR增长分析.md
- docs/03-增长迭代/数据报告与用户反馈.md
- docs/03-增长迭代/增长执行方案.md
- docs/03-增长迭代/迭代计划.md
Recommended next steps:
- /pm-roadmap — Update the product roadmap
- /pm-abtest — Design A/B tests for growth experiments
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.
- 9d ago First seen · 74 lines · 42 tokens per session scan A b90a1b8868c5
analyze-growth is a skill published in the GitHub repository konglong87/superPM (64 stars, last pushed 5d ago), licensed MIT. It adds 42 tokens to every session and 486 once invoked, about $0.0002 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 2026-08-30.
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