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 paid-channel-prioritizergit 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/paid-channel-prioritizer)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/paid-channel-prioritizer"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/paid-channel-prioritizer/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/paid-channel-prioritizer"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/paid-channel-prioritizer.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 | $0.00070 | $0.02653 |
| Opus 5 | $0.00035 | $0.01326 |
| Sonnet 5 | $0.00014 | $0.00531 |
| Haiku 4.5 | $0.00007 | $0.00265 |
Grade A, and why
paid-channel-prioritizer 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 13d 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 — 259 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Paid Channel Prioritizer
Answer the question every early-stage founder asks: "Where should I run ads?" This skill analyzes your product, ICP, competitors, and budget to recommend the right 1-2 channels to start with — plus a 90-day plan to get there.
Core principle: A $3K/month ad budget split across Google, Meta, LinkedIn, and TikTok means $750/channel — not enough for any platform to learn and optimize. This skill picks the best 1-2 channels and concentrates budget where it'll compound fastest.
When to Use
- "Where should I run ads?"
- "Which ad platform is best for us?"
- "I have $X/month for ads — where should I spend it?"
- "Should I do Google Ads or Facebook Ads?"
- "Help me choose a paid channel"
Phase 0: Intake
- Product name + URL — What are you selling?
- Business model — SaaS / Marketplace / E-commerce / Service / App
- B2B or B2C? — Drives channel selection heavily
- ICP — Who are you selling to? (Role, company size, industry)
- Monthly ad budget — Be honest — how much can you spend?
- Average deal size / LTV — What's a customer worth?
- Current acquisition channels — How are you getting customers today? (Organic, referral, outbound, etc.)
- Competitor names — 3-5 competitors
- Landing page ready? — Do you have a dedicated LP or just a homepage?
- Conversion goal — Free trial / Demo / Purchase / Lead magnet download
Phase 1: Channel Scoring
1A: Buyer Intent Analysis
Where does your buyer look when they have a problem?
| Buyer Journey Stage | Likely Channel | Signal |
|---|---|---|
| "I need a tool for X" (active search) | Google Search | High-intent keywords exist |
| "I'm browsing and see something relevant" (passive) | Meta (FB/IG) | Visual/emotional product |
| "I need to solve this at work" (professional) | B2B decision-maker targeting | |
| "Everyone's talking about this" (social proof) | Twitter/X Ads | Category is trending |
| "I watch content about this" (education) | YouTube | Long consideration cycle |
| "I discovered it through content" (entertainment) | TikTok | B2C, young audience, visual |
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.
- 13d ago First seen · 259 lines · 70 tokens per session scan A 89e54688dcb5
paid-channel-prioritizer is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 70 tokens to every session and 2,653 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.
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.
error-handling
Python error handling patterns for FastAPI, Pydantic, and asyncio. Follows "Let it crash" philosophy - raise exceptions, catch at boundaries. Covers HTTPException, global exception handlers, validation errors, background task failures. Use when: (1) Designing API error responses, (2) Handling RequestValidationError…
linting
Python linting with Ruff - an extremely fast linter written in Rust. Use when: (1) Standardizing code quality, (2) Fixing style warnings, (3) Enforcing rules in CI, (4) Replacing flake8/isort/pyupgrade/autoflake, (5) Configuring lint rules and suppressions.
logfire
Structured observability with Pydantic Logfire and OpenTelemetry. Use when: (1) Adding traces/logs to Python APIs, (2) Instrumenting FastAPI, HTTPX, SQLAlchemy, or LLMs, (3) Setting up service metadata, (4) Configuring sampling or scrubbing sensitive data, (5) Testing observability code.
commit-message
Analyze git changes and generate conventional commit messages. Supports batch commits for multiple unrelated changes. Use when: (1) Creating git commits, (2) Reviewing staged changes, (3) Splitting large changesets into logical commits.
python-backend
Python backend development expertise for FastAPI, security patterns, database operations, Upstash integrations, and code quality. Use when: (1) Building REST APIs with FastAPI, (2) Implementing JWT/OAuth2 authentication, (3) Setting up SQLAlchemy/async databases, (4) Integrating Redis/Upstash caching, (5) Refactoring…