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。
Before stating any specific fact about an LLM provider's product — models, pricing, limits, context windows, SDK/API — for OpenAI, Gemini, Claude & others, verify against official docs, not memory.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Verify LLM-provider product facts against official documentation, never
memory. This skill is the multi-provider sibling of Claude Code's bundled
product-self-knowledge — extended to OpenAI, Google Gemini, Anthropic,
Mistral, xAI, DeepSeek, Cohere, and Meta Llama, and portable to every host this
package projects to (not just Claude Code).
This skill is a signpost, not a library. It routes you to the authoritative source and forces a source-cited answer. It does not cache model IDs, context windows, prices, or rate limits — those churn constantly, and a cached copy is exactly the stale "from memory" answer this skill exists to prevent.
prompt-engineering-patterns.model-recommendation (never
recommend another vendor's model over the host's; this skill only reports
facts, it does not steer model choice).image-provider-routing.Route to the stable root and read live from there — do not deep-link to pages that churn. Prefer a provider's machine-readable index where one exists.
| Provider | Docs root | API reference | Product / support |
|---|---|---|---|
| OpenAI (GPT) | platform.openai.com/docs | platform.openai.com/docs/api-reference | help.openai.com |
| Google Gemini | ai.google.dev/gemini-api/docs | ai.google.dev/api | support.google.com (Gemini app) |
| Anthropic (Claude) | docs.claude.com/en/docs (index: /en/docs_site_map.md) | docs.claude.com/en/api/overview | support.claude.com |
| Mistral | docs.mistral.ai | docs.mistral.ai/api | help.mistral.ai |
| xAI (Grok) | docs.x.ai | docs.x.ai/developers | x.ai |
| DeepSeek | api-docs.deepseek.com | api-docs.deepseek.com/api | platform.deepseek.com |
| Cohere | docs.cohere.com (index: docs.cohere.com/llms.txt) | docs.cohere.com/reference | dashboard.cohere.com |
| Meta Llama | llama.com (dev docs: ai.developer.meta.com/docs) | ai.developer.meta.com/docs | llama.com |
Claude Code specifics (install, Node.js requirement, MCP, config):
docs.anthropic.com/en/docs/claude-code/claude_code_docs_map.md.
Hosted access (not a distinct vendor): Azure OpenAI, AWS Bedrock, and
Google Vertex AI resell the underlying vendor's models. Route to BOTH the
underlying vendor's row above AND the cloud's own docs (learn.microsoft.com,
docs.aws.amazon.com/bedrock, cloud.google.com/vertex-ai) — model IDs,
quotas, and regions differ from the vendor's direct API.
llms.txt where present).Every reply that states a provider product fact MUST include:
model-recommendation; this skill reports facts neutrally.product-self-knowledge also fires for Anthropic facts — both route to the
same Anthropic docs, so the overlap is harmless. On every other host this is
the only such skill.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。