Brand

Skill event4u-app/agent-config/dist/agent-src/skills/brand

Universal AI Agent OS — audited skills, governance rules, replayable state. One contract, every host agent.

Install

npx -y skills add event4u-app/agent-config --skill brand

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One thing to look at

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What its author says it does

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Grounded brand decisions from a curated corpus — archetype, voice, naming, colour psychology, logo-style fit, messaging frameworks, archetype→type mapping. Use to ground brand strategy and identity.

SKILL.md

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brand

The grounded source for brand decisions — a second instance of the ADR-061 corpus-grounding layer (corpus-grounding), after design-intelligence. Branding is the layer that constrains UI: the corpus grounds brand strategy and identity decisions (archetype, voice, naming, colour, logo style, messaging, archetype→type filter) as a constraint set the human confirms — never the final brand. No forked engine; this plugs into the shared one via a manifest.

Corpus: 7 tabular CSVs under data/ — 12 brand archetypes, a voice-and-tone matrix, naming patterns, color psychology by industry, logo-style ↔ industry fit, messaging frameworks, and typography-principles (archetype → pairing-filter Grounding, the layer that upgrades typography-system stage-2). Provenance: ATTRIBUTION.md; manifest: data/manifest.json.

When to use

A brand decision needs grounding: which archetype fits, what voice/tone, how to name, which colour direction, which logo style, which messaging framework, or which type pairing-filter an archetype implies.
Before brand-strategy / brand-identity commit to a direction — those skills consult this corpus first.
When typography-system needs the brand-aware (archetype → pairing-filter) upgrade — query the typography domain here.

Procedure: consult the brand corpus

Ground or search (paths resolve skill-relative; works from any cwd):

./scripts-run <skills-root>/corpus-grounding/scripts/ground search \
  --manifest <skills-root>/brand/data/manifest.json \
  "<brand brief: sector + intent + audience>" \
  [--domain archetype|voice|naming|color|logo|messaging|typography] \
  [--filter "Archetype Fit=Ruler"] [--json]

<skills-root> is ~/.claude/skills/ for Claude Code installs, src/skills/ inside this repo.

Read confidence + every evidence_gap line before trusting any row — surface them; the human signs off on what the corpus could NOT support.
Propose grounded options (archetype + voice + colour + logo + messaging), each cited per corpus row, with alternatives — the human confirms.
The confirmed selections become the brand token + voice constraint set that brand-to-tokens, brand-consistency, and pack-ai-image's brand-asset generation consume.

Output format

Grounded brand candidates per domain (archetype, voice, naming, colour, logo style, messaging, type filter) — each selection cited per corpus row.
The grounded output's confidence label + every evidence_gap line, verbatim.
Alternatives per domain so the human can swap before confirming.

Do NOT

Do NOT let the corpus author final brand copy or names — it supplies constraint sets and patterns; final strings are agent-written and human-confirmed.
Do NOT fork the engine — plug in via the manifest (ADR-061 §2).
Do NOT override the consumer's existing brand tokens / voice profile with corpus rows — consumer brand is the source of truth; the corpus fills gaps (see brand-source-of-truth).
Do NOT hide low confidence — the user signs off on the gaps too.

Gotchas

Corpus grounds pre-action selection — not mid-task reference and not output validation (brand-consistency owns validation).
Keep queries brand-shaped ("luxury law firm rebrand", "playful kids snack brand") — generic words land on the default archetype domain.
An empty result is a legitimate outcome — surface the evidence gap and proceed on priors; never widen filters to force a hit.
BM25 drops tokens ≤2 chars — pad short queries ("B2B", "AI") with companions.

Policies

Provenance: ATTRIBUTION.md — original-authored corpus from public brand frameworks; shared engine attributed in design-intelligence/ATTRIBUTION.md.
Refresh: quarterly per the manifest; re-review archetype↔type rows when the font-pairings Reference refreshes.