agency-brand-scoping

agency-brand-scoping is a skill for Claude Code from PicsArt/gen-ai-skills. It costs 13 tokens per session (2,363 once invoked), scanned A, original, MIT.

A discovery process that collects a client’s brand information and turns it into a reusable brand-system file plus five visual directions. It is meant for deciding the look of a project before producing final campaign materials.

In plain words
What is it for?
Use it for pitches, new client kickoffs, rebrands, or other early-stage work involving websites, decks, competitors, audiences, and brand tone.
Why use it?
Early brand work often leaves the visual direction unclear, which can lead to wasted production effort. Comparing several directions helps a client and agency choose a path before committing to finished assets.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: positional $N argument.

Part of the picsart plugin — 23 skills, 2 MCP servers shipped together

Good fit Use it for pitches, new client kickoffs, rebrands, or other early-stage work involving websites, decks, competitors, audiences, and brand tone.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/picsart/gen-ai-skills/agency-brand-scoping
Install

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.

Any agent
npx skills add PicsArt/gen-ai-skills --skill agency-brand-scoping
Clone the repo
git clone --depth 1 https://github.com/PicsArt/gen-ai-skills

Made for: Claude Code.

Or install picsart, the plugin that ships this one along with the rest of its 23 skills, 2 MCP servers.

Wrote 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.

agentmods badge for agency-brand-scoping

README.md
[![agentmods](https://agentmods.dev/badge/skills/picsart/gen-ai-skills/agency-brand-scoping/github.svg)](https://agentmods.dev/skills/picsart/gen-ai-skills/agency-brand-scoping)
Your own site
<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.

agentmods 80×15 button for agency-brand-scoping

Your own site · 80×15
<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>
Per session 13 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,363 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 12d ago against content hash 5e5e9b47436c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

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.

skills/agency-brand-scoping/SKILL.md · 183 lines

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):

  1. Client name + slug — used for folder + manifest tags (e.g. acme-fintech)
  2. Brand references — URL, existing deck, Figma file, or "no brand yet, we're defining it"
  3. Competitors / comparable brands — 2-3 names; informs what NOT to look like
  4. Audience + tone — who buys, what feeling ("premium + restrained" vs "bold + irreverent")
  5. Deliverable type the scope is for — pitch deck, campaign, launch film, product shoot (informs aspect ratios)
  6. 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

Read the full file on GitHub · 183 lines

Changes

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.

  1. 12d ago First seen · 183 lines · 13 tokens per session scan A 5e5e9b47436c

Subscribe to this mod's changes

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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