一键导入
improve-codebase-architecture
Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Use when building or improving HTML/CSS artifacts, React pages, dashboards, landing pages, explainers, demos, SVG diagrams, UI prototypes, or visual outputs where design quality, subject-specific treatment, responsive behavior, and render verification matter.
General Python development skill for designing, implementing, refactoring, debugging, testing, validating, and reviewing Python code. Use for Python 3.11+ projects, especially modern pyproject-based repos using uv, Ruff, pytest, mypy, Pydantic v2, pydantic-settings, Typer, and Loguru. Applies the house Python stack uniformly while discovering local contracts.
Use when the user asks to use a kanban process, track development work on a GitHub board, work from the agent board, proactively track tasks and deferred findings, runs `/kanban-process`, or when the project is already configured to use this workflow.
Use at the start of every Fable session. Fable is the brain: decompose, dispatch, judge, and talk to the user. Codex CLI does the work: exploration, bulk reads, tests, builds, implementation, reviews, and other token-heavy units.
Use when spawning Codex subagents or Codex threads and choosing among GPT 5.6 Luna, Terra, and Sol with the appropriate effort. Use this with orchestrating-subagents whenever delegation involves model overrides, reasoning effort, Explore agents, checker/fixer loops, or fan-out work.
Use when an AI agent is itself performing a pull request review (not coaching a human, not fetching the PR). Covers agent-specific tactics: context budget, tool escalation triggers, Explore subagent dispatch (single sidecar and parallel fan-out), when to emit "I cannot review this responsibly", auto-memory integration, and agent failure modes (confabulation, tool-call theater, delegated certainty laundering, evidence laundering, patch sycophancy, premature fan-out). Complements reviewing-pull-requests (universal doctrine) and pr-review (operational PR fetch + per-layer comparison).
| name | improve-codebase-architecture |
| description | Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick. |
| disable-model-invocation | false |
Surface architectural friction and propose deepening opportunities — refactors that turn shallow modules into deep ones. The aim is testability and AI-navigability.
This command is informed by the project's domain model and built on a shared design vocabulary:
/codebase-design skill for the architecture vocabulary (module, interface, depth, seam, adapter, leverage, locality) and its principles (the deletion test, "the interface is the test surface", "one adapter = hypothetical seam, two = real"). Use these terms exactly in every suggestion — don't drift into "component," "service," "API," or "boundary."CONTEXT.md gives names to good seams; ADRs in docs/adr/ record decisions this command should not re-litigate.Read the project's domain glossary (CONTEXT.md) and any ADRs in the area you're touching first.
Then use the Agent tool with subagent_type=Explore to walk the codebase. Don't follow rigid heuristics — explore organically and note where you experience friction:
Apply the deletion test to anything you suspect is shallow: would deleting it concentrate complexity, or just move it? A "yes, concentrates" is the signal you want.
Write a self-contained HTML file to the OS temp directory so nothing lands in the repo. Resolve the temp dir from $TMPDIR, falling back to /tmp (or %TEMP% on Windows), and write to <tmpdir>/architecture-review-<timestamp>.html so each run gets a fresh file. Open it for the user — xdg-open <path> on Linux, open <path> on macOS, start <path> on Windows — and tell them the absolute path.
The report uses Tailwind via CDN for layout and styling, and Mermaid via CDN for diagrams where a graph/flow/sequence reliably communicates the structure. Mix Mermaid with hand-crafted CSS/SVG visuals — use Mermaid when relationships are graph-shaped (call graphs, dependencies, sequences), and hand-built divs/SVG when you want something more editorial (mass diagrams, cross-sections, collapse animations). Each candidate gets a before/after visualisation. Be visual.
For each candidate, render a card with:
Strong, Worth exploring, Speculative, rendered as a badgeEnd the report with a Top recommendation section: which candidate you'd tackle first and why.
Use CONTEXT.md vocabulary for the domain, and the /codebase-design vocabulary for the architecture. If CONTEXT.md defines "Order," talk about "the Order intake module" — not "the FooBarHandler," and not "the Order service."
ADR conflicts: if a candidate contradicts an existing ADR, only surface it when the friction is real enough to warrant revisiting the ADR. Mark it clearly in the card (e.g. a warning callout: "contradicts ADR-0007 — but worth reopening because…"). Don't list every theoretical refactor an ADR forbids.
See HTML-REPORT.md for the full HTML scaffold, diagram patterns, and styling guidance.
Do NOT propose interfaces yet. After the file is written, ask the user: "Which of these would you like to explore?"
Once the user picks a candidate, run the /grilling skill to walk the design tree with them — constraints, dependencies, the shape of the deepened module, what sits behind the seam, what tests survive.
Side effects happen inline as decisions crystallize — run the /domain-modeling skill to keep the domain model current as you go:
CONTEXT.md? Add the term to CONTEXT.md. Create the file lazily if it doesn't exist.CONTEXT.md right there./codebase-design skill and use its design-it-twice parallel sub-agent pattern.