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 rampstackco/claude-skills --skill brand-discoverygit clone --depth 1 https://github.com/rampstackco/claude-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/rampstackco/claude-skills/brand-discovery)<a href="https://agentmods.dev/skills/rampstackco/claude-skills/brand-discovery"><img src="https://agentmods.dev/badge/skills/rampstackco/claude-skills/brand-discovery/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/rampstackco/claude-skills/brand-discovery"><img src="https://agentmods.dev/badge/skills/rampstackco/claude-skills/brand-discovery.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 | $0.00132 | $0.02088 |
| Opus 5 | $0.00066 | $0.01044 |
| Sonnet 5 | $0.00026 | $0.00418 |
| Haiku 4.5 | $0.00013 | $0.00209 |
Grade A, and why
brand-discovery 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 10d 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 — 204 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Brand Discovery
Upstream of every brief, identity, and content plan. Discovery answers four questions: who the brand is for, what they need, who else is competing for that need, and where the brand could plausibly stand that competitors do not.
When to use
- The very first phase of a new brand or website project
- Understanding an audience before any creative work begins
- Mapping competitors and category dynamics
- Surfacing the problem space the brand will operate in
- Generating positioning territories before brief or ideation
- When a creative brief was requested but the inputs are missing
When NOT to use
- The audience and category are already well-understood (jump to
creative-brieforbrand-ideation) - Validating a specific design or feature with users (use
usability-testing) - Mapping the customer journey of an existing audience (use
journey-mapping) - Generating brand names or visual directions (use
brand-ideation)
Required inputs
- The product, service, or organization being branded
- Whatever is already known about the audience and category (often very little)
- Access to existing materials (sales calls, support tickets, reviews, analytics)
- Any constraints (parent brand, regulatory, geographic)
- A timeline (a 1-week discovery looks different than a 6-week one)
The framework: 4 dimensions
Discovery covers four dimensions. Each has its own sources, methods, and outputs.
1. Audience
Who specifically does this serve?
Layers to surface:
- Demographic: Age range, geography, language, life stage, income (only if relevant; do not over-collect demographics)
- Psychographic: Values, motivations, beliefs, fears
- Behavioral: What they currently do to address the problem, what tools they use, where they spend time online and offline
- Jobs-to-be-done: The functional, emotional, and social jobs they hire a brand to perform
Sources:
- Existing customer interviews (5 to 8 ideal)
- Sales call recordings or transcripts
- Support ticket themes
- Review and forum analysis (Reddit, Trustpilot, App Store, niche communities)
- First-party analytics (search console queries, on-site search, top pages)
- Social listening (what they post about the category)
What ships with it
2 files 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.
- 10d ago First seen · 204 lines · 132 tokens per session scan A 1826d52344ec
brand-discovery is a skill published in the GitHub repository rampstackco/claude-skills (832 stars, last pushed 2d ago), licensed MIT. It adds 132 tokens to every session and 2,088 once invoked, about $0.0007 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.
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