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 icp-website-auditgit 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/icp-website-audit)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/icp-website-audit"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/icp-website-audit/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/icp-website-audit"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/icp-website-audit.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 | $0.00083 | $0.02913 |
| Opus 5 | $0.00042 | $0.01456 |
| Sonnet 5 | $0.00017 | $0.00583 |
| Haiku 4.5 | $0.00008 | $0.00291 |
Grade A, and why
icp-website-audit 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 — 365 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ICP Website Audit
The complete "how do buyers experience our site vs the competition?" workflow. Chains persona building, website evaluation, and competitive comparison into a single end-to-end audit.
Quick Start
Run an ICP website audit for [company]. Site: [url]. Compare against [competitor 1] and [competitor 2].
With existing personas:
Run an ICP website audit for [client]. Personas already exist. Compare against [competitor urls].
Inputs
| Input | Required | Source |
|---|---|---|
| Company name | Yes | User provides |
| Company URL | Yes | User provides |
| Competitor URLs | Yes (1-3) | User provides, or discovered in Phase 1 |
| Client context file | Optional | clients/<client>/context.md |
| Existing personas | Optional | clients/<client>/personas/personas.json |
Step-by-Step Process
Phase 1: Persona Setup
Check if personas already exist:
clients/<client>/personas/personas.json
If personas exist: Load them, confirm they look current, and list them for the user. Skip to Phase 2.
If no personas exist: Run buyer-persona-generator:
- Research the company — what they sell, who they serve, pricing model, stage
- Identify 4-6 ICP segments from website, case studies, reviews, job postings
- Build detailed synthetic personas with full profiles
- Save to
clients/<client>/personas/
Output from this phase:
clients/<client>/personas/personas.json(machine-readable)clients/<client>/personas/personas.md(human-readable)clients/<client>/personas/segments.md(summary table)
Phase 2: Website Scorecard Review
Run icp-website-audit in scorecard mode against the client's own site.
- Crawl the client's site — homepage, pricing, product, solutions, about, case studies, blog, docs
- Check external presence — search results, review sites, social proof
- Run each persona through the site, scoring on:
- First Impression (1-10)
- Messaging Relevance (1-10)
- Trust & Credibility (1-10)
- Clarity & Navigation (1-10)
- Objection Handling (1-10)
- Overall (1-10)
- Cross-persona synthesis — consensus issues, segment-specific gaps, messaging disconnects
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 · 365 lines · 83 tokens per session scan A 0ebc08ba79bd
icp-website-audit is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 83 tokens to every session and 2,913 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.
Other skills, from other repositories
excalidraw-ai
Create professional Excalidraw diagrams by generating JSON directly. This skill provides the Excalidraw JSON schema reference and professional icon libraries for AI agents to autonomously create diagrams without templates.
scientific-schematics
Create publication-quality scientific diagrams using Nano Banana 2 AI with smart iterative refinement. Uses Gemini 3.6 Flash for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and…
visual-qa
Runs rigorous visual QA across web, terminal, and paginated surfaces with screenshot evidence and a verdict. Use for any UI build or change, or when asked whether a page, component, or TUI looks right.
frontend
Builds, styles, and polishes web UI and UX. Use for any frontend, page, component, styling, layout, animation, or visual-quality task, or when asked to make an interface look or feel a certain way.
ambience-skill
Layer A ambience-and-typographic-motion reference anchored to the react-bits catalog (reactbits.dev). Stacks on any style skill whenever work adds a hero atmosphere, an animated or shader background, a typographic reveal (split, blur, shimmer, typewriter, count-up, marquee), scroll storytelling, or card surface…
interaction-skill
Layer A interaction-mechanics reference anchored to the beui.dev catalog. Stacks on any style skill whenever work adds or changes motion or interaction — micro-interactions, animated components, transitions, gestures, hover/press/state feedback, loading/success/error morphs, 'make it feel alive'. Mandates reading the…