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A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Bootstrap and manage the personal .lightbridge namespace — per-project config at ~/.lightbridge/projects/<project-key>/config.toml (docs-index, repo-links, research, plans, …) and the rest of the user-level ~/.lightbridge/ tree (handoffs, plans, repos.toml). Use when setting up lightbridge config for a repo, enabling or adding a config section, asking what .lightbridge supports, wiring a new config feature, or locating user-level lightbridge state.
Explain an existing agentic system — a codebase where an AI agent is the central "CPU" surrounded by agent-native organs (reasoning loop, memory, context, tools, skills, MCP, subagents, hooks) — or design one from requirements. Covers agent runtimes/harnesses and capability/steering packs. Use when the user invokes it by name (`agentic-architecture`) or near-match.
The agent-experience ("AX") lens for any interface an AI agent drives — a CLI, MCP server, HTTP/REST API, or library/SDK. Judge an existing surface against the AX principles and prescribe prioritized fixes, or apply the principles while designing a new agent-facing surface. For a descriptive whole-surface doc across all audiences (end user / developer / agent), use `surface-architecture` instead. Use when the user invokes it by name (`ax-interface`) or near-match ("AX analysis", "agent experience of …", "agent-friendly interface").
The reconciliation pass between a settled design and the first line of code. Read the design docs, hunt the places they disagree with each other and with the chosen framework, then compile the object model that must satisfy all of them at once — turning prose rules into machine-checked invariants and amending upstream docs it contradicts. Use when design is settled and you are about to build, or when the user invokes it by name (`codebase-blueprint`) or near-match.
Explain an existing codebase's data architecture — where data rests (stores, schema) and how it moves (dataflow, lineage) — or design one from requirements. One Markdown doc with Mermaid diagrams. Use when the user invokes it by name (`data-architecture`) or near-match.
Decompose a function, method, class, or module of an existing codebase into a runnable notebook that explains it top-down — each piece executed on concrete inputs with real output shown inline. Use when the user invokes it by name (`explain-as-notebook`) or near-match mentioning.
| name | grill-with-docs |
| description | A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go. |
| disable-model-invocation | false |
| metadata | {"version":"2026-07-02"} |
Run a /grilling session, using the /domain-modeling skill.
Adapted from mattpocock/skills (MIT).
