Goose Skills is a library of workflows and data APIs that lets coding agents handle growth and go-to-market work such as advertising, social media, content, SEO, lead generation, and customer research. It is intended for teams using Claude Code, Cursor, Codex, and similar agents. The catalogue entries are its reusable skills.
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 gooseworks-ai/goose-skills --skill feature-launch-playbookgit clone --depth 1 https://github.com/gooseworks-ai/goose-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/gooseworks-ai/goose-skills/feature-launch-playbook)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/feature-launch-playbook"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/feature-launch-playbook/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/gooseworks-ai/goose-skills/feature-launch-playbook"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/feature-launch-playbook.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 | $0.00080 | $0.01927 |
| Opus 5 | $0.00040 | $0.00963 |
| Sonnet 5 | $0.00016 | $0.00385 |
| Haiku 4.5 | $0.00008 | $0.00193 |
Grade A, and why
feature-launch-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 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.
How it starts
The opening of the file, as written. The whole thing — 286 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Launch Playbook
Turn a feature spec or product update into a complete launch kit — every asset you need to announce, from changelog to cold email insert. One input, all outputs.
Built for: PMMs or founders who ship features faster than they can write about them. The goal is to go from "feature merged" to "launch assets ready" in one session.
When to Use
- "We just shipped [feature] — help me launch it"
- "Write launch copy for [feature/update]"
- "I need a changelog entry, email, and LinkedIn post for [feature]"
- "Generate the full launch kit for [product update]"
- "Turn this feature spec into marketing assets"
Phase 0: Intake
Feature Context
- Feature name — What are you launching?
- One-paragraph description — What does it do? (Can be a Notion doc, PRD excerpt, or plain text)
- Who benefits most? — Which ICP segment cares about this? (e.g., "growth teams running outbound")
- Problem it solves — What was painful before this existed?
- Key capability — The single most impressive thing it does (for the headline)
Launch Context
- Launch tier — How big is this?
- Tier 1 (Major): New product line, major feature, pricing change → Full launch kit
- Tier 2 (Medium): Significant feature, new integration → Email + social + changelog
- Tier 3 (Minor): Small improvement, bug fix → Changelog + social mention
- Launch date — When does this go live?
- CTA — What should the reader do? (Try it, book a demo, read docs, upgrade)
- Visual assets available? — Screenshots, GIFs, demo video URL?
Tone & Voice
- Brand voice — Technical/developer, conversational/founder-led, enterprise/professional?
- Any messaging to avoid? — Competitor names, specific claims, regulated language?
Phase 1: Core Messaging (Foundation)
Before generating assets, define the messaging foundation:
Feature Positioning Block
HEADLINE: [Outcome-driven, not feature-driven]
Bad: "Introducing Advanced Filtering"
Good: "Find your best leads in seconds, not hours"
SUBHEAD: [What it is + who it's for]
"[Feature name] lets [audience] do [capability] so they can [outcome]."
PROOF POINT: [Metric or before/after comparison]
"In beta, [customer] saw [X% improvement / saved X hours]."
CTA: [Single clear action]
"[Try it now / See it in action / Book a demo]"
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.
- 9d ago First seen · 286 lines · 80 tokens per session scan A 10d5ecb81963
feature-launch-playbook is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 80 tokens to every session and 1,927 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 2026-09-03.
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