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 update-brand-kitgit 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/update-brand-kit)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/update-brand-kit"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/update-brand-kit/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/update-brand-kit"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/update-brand-kit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
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 →
- medium Excessive Agency · line 28 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00126 | $0.01616 |
| Opus 5 | $0.00063 | $0.00808 |
| Sonnet 5 | $0.00025 | $0.00323 |
| Haiku 4.5 | $0.00013 | $0.00162 |
Grade A, and why
update-brand-kit 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Update Brand Kit
Purpose
Keep a brand kit correct and rich by talking to the user. A brand kit is the canonical context an ad/content-generation pipeline reads, so what's in it directly shapes every downstream generation. Reach for this whenever the user wants to set or refine brand positioning/voice/audience, add standing do/don't guidance, manage the product list, or attach product photos.
This skill is the portable domain model — the fields, the semantics, the rules. How you actually persist a change is the host's concern: a brand-kit API, a CLI, or a brand-kit document in a workspace. The field model, semantics, and caps below hold regardless of which backend stores the kit.
Inputs
- A natural-language request — free-form ("make the voice warmer and more technical", "we sell to ops teams not consumers", "add our Pro plan at $49"). You translate this into the field model below; do not ask the user to name fields.
- Optionally, a brand identifier or name — when the user owns more than one brand, you need to know which one. If they only have one, use it.
- Optionally, a folder of product photos to attach to a product.
The brand-kit field model
These are the context fields. Treat each edit as a partial update (see semantics): set only what's changing.
description— what the brand does, in 1–2 sentences.audience— target audience / ICP.voice— tone of the copy.instructions— standing guidance applied to every generation (e.g. "always show the product in use", "never use red"). High-leverage — set this whenever the user describes a recurring do/don't, not a one-off.brand_type— one of: product, saas, service, agency, restaurant, fashion, beauty, fitness, finance, education, health.value_props— short selling points; the kit keeps the first 5.primary_color/accent_color— hex like #1a2b3c (validate the format).
Products (a list on the kit) carry: name (required), description, link,
pricing (free text, e.g. "$49"), offers (e.g. "20% off launch week"),
notes (markdown), and an ordered list of images.
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 · 125 lines · 126 tokens per session scan A 9769173abb30
update-brand-kit is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 126 tokens to every session and 1,616 once invoked, about $0.0006 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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