Use when reviewing UI for accessibility — WCAG 2.2 AA, keyboard nav, focus, ARIA, contrast, screen-reader semantics — even on 'is this a11y-OK?' or 'mach das barrierefrei'.
日本語の概要は準備中です。原文の説明を表示しています。
Ground a brand strategy from the corpus — archetype, opposable positioning, voice and tone, messaging framework. Use to decide who a brand is for, what it stands for, and how it sounds.
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Grounding skill. Consults the brand corpus to surface archetype, positioning, voice/tone, and messaging constraints. Output is a constraint set the human confirms — never final brand copy — then handed to brand-identity and brand-to-tokens.
Pressure-test the brief. Is the audience named (not "everyone")? Is the difference opposable (could a competitor claim the opposite)? Is there at least one proof point? If any are missing, challenge — do not proceed on a vague brief.
Ground via the corpus. Run the corpus engine for each required domain. Start with archetype, then voice, then messaging:
./scripts-run <skills-root>/corpus-grounding/scripts/ground search \
--manifest <skills-root>/brand/data/manifest.json \
"<sector + audience + intent>" --domain archetype --json
Repeat with --domain voice and --domain messaging. Each call returns ranked rows with confidence and evidence_gap.
Read confidence and evidence gaps. Before trusting any row, read confidence and every evidence_gap entry verbatim. Low-confidence rows must be surfaced as gaps — never silently promoted.
Draft the constraint set. Produce:
Surface gaps and low-confidence calls. Name every evidence gap and every row below the confidence threshold. Flag where the corpus was thin.
Human confirms. Present the full constraint set. Wait for confirmation before handing off. Do not proceed autonomously.
Hand off. Pass the confirmed constraint set to brand-identity (identity execution) and brand-to-tokens (DTCG token emission).
evidence_gap from the corpus verbatim.brand — the corpus this skill grounds against.brand-identity — consumes the confirmed strategy.brand-to-tokens — emits the DTCG token source of truth.corpus-grounding — the shared engine.まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Use when reviewing UI for accessibility — WCAG 2.2 AA, keyboard nav, focus, ARIA, contrast, screen-reader semantics — even on 'is this a11y-OK?' or 'mach das barrierefrei'.
日本語の概要は準備中です。原文の説明を表示しています。
Use when defining or auditing the activation event — aha-moment selection, retention correlation, falsifiable definition. Triggers on 'what is our aha moment', 'redefine activation'.
日本語の概要は準備中です。原文の説明を表示しています。
Use when capturing an architectural decision — file naming, next ADR number, Status / Context / Decision / Consequences, index regen; fires even without saying 'ADR'.
日本語の概要は準備中です。原文の説明を表示しています。
Adversarial critique — devil's advocate, stress-test, honest teardown ('poke holes', 'be brutal', 'was hältst du davon'); explicit request only. Routine code or design review → code-review.
日本語の概要は準備中です。原文の説明を表示しています。
Use when reading, creating, or updating agent documentation, module docs, roadmaps, or AGENTS.md. Understands the full .augment/, agents/, and copilot-instructions structure.
日本語の概要は準備中です。原文の説明を表示しています。
Use for an adversarial red-team / blue-team / auditor review of an AI agent's CONFIG + behaviour (rules, skills, MCP, hooks, permissions) — attack-chain → defensive-gap list, not a code audit.
日本語の概要は準備中です。原文の説明を表示しています。