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 demo-buildergit 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/demo-builder)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/demo-builder"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/demo-builder/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/demo-builder"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/demo-builder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Agent Snooping · line 163 Skill accesses MCP server configuration files (mcp.json). MCP configs contain server URLs, authentication tokens, and tool definitions — reading them allows the skill to discover and potentially abuse other tool integrations.Fix: Remove all code or instructions that read MCP configuration files (mcp.json). MCP server details should be managed by the agent runtime, not read by individual skills.
- high Memory Poisoning · line 285 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
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 | $0.00046 | $0.04573 |
| Opus 5 | $0.00023 | $0.02286 |
| Sonnet 5 | $0.00009 | $0.00915 |
| Haiku 4.5 | $0.00005 | $0.00457 |
Grade A, and why
demo-builder scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- **API:** a hosted endpoint with example curl commands in the report How it starts
The opening of the file, as written. The whole thing — 422 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Demo Builder
Build personalized demo assets for prospects using the founder's product API/MCP/SDK. Send a working prototype that solves the prospect's actual problem — with a comparison report and live demo link.
When to Use
- User provides a prospect company name or URL and wants a demo built for them
- User asks to "build a demo", "create an asset", or "personalize outreach" for a specific company
- User has a product with API access, SDK, MCP server, or CLI and wants to demonstrate it to a prospect
- User has completed a lead generation run and wants to act on the results
- User asks "what do I do with these leads", "how do I reach out", or "help me with outreach"
Prerequisites
- API access, MCP access, SDK, or CLI for the user's product — the agent needs to be able to actually build something
- Access to the product's documentation (API docs URL, SDK readme, or MCP tool list)
Phase 1: Identify the Prospect
This skill supports two input paths:
Path A: User provides a prospect directly (primary path)
If the user provides a company name, website URL, or prospect details:
- Accept the prospect as-is — no lead data required
- Proceed directly to Phase 2 (Research the Prospect)
Ask the user:
"I'll build a working demo for [Company]. Before I start, I need to know:
- What does your product do? (one-liner)
- What problem does it solve for companies like [Company]?
- Where are your API docs / SDK / MCP tools?"
If the user has already provided product context (from lead-discovery or prior conversation), skip questions they've already answered.
Path B: User has signal data from prior lead generation runs
If the user has csv outputs from signal skills, help them pick the best prospect:
- Read the csv outputs and identify top candidates by looking for multi-signal leads, switching signals, build-vs-buy signals, high interaction scores, community pain signals, or company clusters
- Shortlist 3-5 candidates with signal sources, key signal, and demo feasibility
- Ask the user to pick one
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 · 422 lines · 46 tokens per session scan A bd3fefc59de2
demo-builder is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 46 tokens to every session and 4,573 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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