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 Gingiris-1031/gingiris-skills --skill github-stars-playbookgit clone --depth 1 https://github.com/Gingiris-1031/gingiris-skillsWrote 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/gingiris-1031/gingiris-skills/github-stars-playbook)<a href="https://agentmods.dev/skills/gingiris-1031/gingiris-skills/github-stars-playbook"><img src="https://agentmods.dev/badge/skills/gingiris-1031/gingiris-skills/github-stars-playbook.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 | $0.00063 | $0.01014 |
| Opus 5 | $0.00032 | $0.00507 |
| Sonnet 5 | $0.00013 | $0.00203 |
| Haiku 4.5 | $0.00006 | $0.00101 |
Grade A, and why
github-stars-playbook 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 2d 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Stars — 14-Day Evidence-Driven Sprint
Use stars as a proxy for qualified developer interest, never as the final business outcome. Track installation, activation, repeat use and contribution beside stars.
Intake gate
Collect before planning:
- repository URL, license and target developer;
- working quickstart verified on a clean machine;
- one reproducible demo and one differentiator;
- current views, unique cloners, stars, issues, contributors and activation event;
- three direct competitors and their latest launch/change dates;
- available founder, engineering and community capacity.
Do not launch if a new developer cannot understand the value and complete the quickstart in 10 minutes.
Measurement contract
Create one row per channel:
date | source | post URL | repo views | stars | clones | installs | activated | retained D7 | contributors
Report view → star, star → install, install → activation, and activation → D7 retained. Do not attribute organic GitHub traffic to a campaign without source evidence.
Competitor-window scan
Before selecting the launch date:
- Review the three competitors' release notes, X, Reddit, Hacker News, Product Hunt and GitHub activity from the last 30 days.
- Record their positioning, strongest proof asset, community response and unresolved complaints.
- Avoid launching into a dominant competitor announcement unless the product is a credible alternative to that exact news.
- Use a quiet window or a category event where the repository adds a distinct point of view.
Historical Gingiris OSS launch evidence shows that timing against the competitor/news window materially changes distribution; it is not enough to post everywhere on a fixed calendar.
README conversion surface
The first screen must contain:
- one-line outcome for a named developer;
- reproducible demo or result;
- three differentiators at most;
- quickstart that works when copied;
- trust signals: license, security/privacy posture, maintainers and community link.
What ships with it
5 files 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.
- 2d ago Changed · +65 lines · +8 tokens per session 05d7d5b57623
- 7d ago First seen · 52 lines · 55 tokens per session scan A 360791ea7da2
github-stars-playbook is a skill published in the GitHub repository Gingiris-1031/gingiris-skills (77 stars, last pushed 2d ago), licensed MIT. It adds 63 tokens to every session and 1,014 once invoked, about $0.0003 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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