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 PicsArt/gen-ai-skills --skill agency-brand-scopinggit clone --depth 1 https://github.com/PicsArt/gen-ai-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/picsart/gen-ai-skills/agency-brand-scoping)<a href="https://agentmods.dev/skills/picsart/gen-ai-skills/agency-brand-scoping"><img src="https://agentmods.dev/badge/skills/picsart/gen-ai-skills/agency-brand-scoping/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/picsart/gen-ai-skills/agency-brand-scoping"><img src="https://agentmods.dev/badge/skills/picsart/gen-ai-skills/agency-brand-scoping.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00013 | $0.02363 |
| Opus 5 | $0.00006 | $0.01182 |
| Sonnet 5 | $0.00003 | $0.00473 |
| Haiku 4.5 | $0.00001 | $0.00236 |
Grade A, and why
agency-brand-scoping 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 12d 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 — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agency brand scoping
A fast discovery pass for a new client: gather brand signals (site, deck, competitors, audience, tone), lock them into a reusable brand-system.json file, and produce 5 on-direction visual explorations to validate with the client before any production spend.
URL / deck in → brand-system.json + 5 direction variations out. One hour, under $1 in generation cost, reusable across the rest of the engagement.
When to Use
- Responding to an RFP and need 5 distinct visual directions for the first review
- Net-new client pitch — you've read the brief, now you need on-brand sketches
- Kickoff phase of a signed engagement, before production generations start
- Scoping a rebrand: grab the existing brand, propose 5 evolution paths
- Any moment where "what does this brand look like in AI generation" is the open question
Do not use for finished campaign assets — this is discovery only. Lock the system here, then run agency-pitch-mockups or agency-multi-brand-pack for deliverables.
Prerequisites
Ask the user (batch in one message):
- Client name + slug — used for folder + manifest tags (e.g.
acme-fintech) - Brand references — URL, existing deck, Figma file, or "no brand yet, we're defining it"
- Competitors / comparable brands — 2-3 names; informs what NOT to look like
- Audience + tone — who buys, what feeling ("premium + restrained" vs "bold + irreverent")
- Deliverable type the scope is for — pitch deck, campaign, launch film, product shoot (informs aspect ratios)
- Confidentiality — is this NDA? If yes, never name the client in public Drive folders or prompts
If the user gives a URL or deck, read/fetch it first and extract palette, typography impression, imagery style, and tone words. Propose the brand-system.json back for confirmation before generating.
How to Run
1. INGEST → read URL / deck / Figma, extract signals
2. DRAFT → propose brand-system.json (palette, type-feel, imagery, tone, do-nots)
3. CONFIRM → user locks the system; save to clients/<slug>/brand-system.json
4. ESTIMATE → gen-ai pricing on the 5-direction batch (< $1 target)
5. GENERATE → 5 directions, each with a single-word descriptor tag
6. REVIEW → contact-sheet the 5 outputs, get client pick
7. LOCK → winning direction becomes clients/<slug>/brand.md for all future work
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.
- 12d ago First seen · 183 lines · 13 tokens per session scan A 5e5e9b47436c
agency-brand-scoping is a skill published in the GitHub repository PicsArt/gen-ai-skills (4 stars, last pushed 15d ago), licensed MIT. It adds 13 tokens to every session and 2,363 once invoked, about $0.0001 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 2026-08-31.
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