「exec」の検索結果

Use when implementing a Python feature, adding CLI commands, writing pytest suites, reviewing Python code, debugging, or refactoring. The primary Python engineering workflow orchestrator — classifies the task and delegates through this plugin's own specialist agents (architect → implement → test → review), sized to the task. Delegates to python-cli-architect (implementation), python-pytest-architect (tests), code-reviewer (review), python-cli-design-spec (architecture). Triggers on any Python task requiring specialist agent coordination or multi-agent execution.

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Use when writing asyncio Python code — async/await coroutines, concurrent I/O with asyncio.gather, task creation and cancellation, semaphore rate limiting, producer-consumer queues, async context managers, async generators, WebSocket servers, aiohttp web scraping, async database operations, run_in_executor for blocking calls, or testing async code with pytest-asyncio. Covers FastAPI and aiohttp patterns, synchronization primitives, timeout handling, and common pitfalls like event loop blocking and missing await.

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Validates and corrects Python shebangs and PEP 723 inline script metadata by applying four shebang-selection rules. Use when auditing or fixing shebangs in Python files — choosing between plain python3 and the uv shebang for standalone scripts with external dependencies, adding or removing PEP 723 metadata blocks to match actual import requirements, checking execute bit presence, or avoiding redundant transitive dependencies when typer is declared.

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Executes a four-phase feature addition workflow (Discovery, Planning, TDD Implementation, Verification) for Python projects. Use when adding a new feature end-to-end — discovering project structure and integration points, drafting a feature spec with MoSCoW-prioritized requirements and BDD acceptance criteria, implementing via test-first TDD cycles, then verifying with ruff lint, ty type checks, and behavior-focused regression and contract coverage.

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Assess a plugin and produce an executable refactoring design, task plan, and context manifest. Use when preparing systematic plugin refactoring.

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Execute an assessor task file and every generated follow-up in dependency order. Use when a refactoring task file already exists.

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Create and configure slash commands for Claude Code — the legacy .claude/commands/ format. Use when asked to "create a slash command", "add a command", "write a custom command", "define command arguments", "use command frontmatter", "organize commands", "create command with file references", "interactive command", "use AskUserQuestion in command", or for guidance on slash command structure, YAML frontmatter fields, dynamic arguments, bash execution in commands, user interaction patterns, or command development best practices. Commands are the legacy format superseded by skills — for new development prefer /plugin-creator:skill-creator

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Hook system fundamentals — all events, configuration structure, matchers per event type, environment variables, execution behavior, security, and debugging. Use when creating hooks, understanding hook events, matchers, configuration locations, environment variables, or troubleshooting hook issues.

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Assess and refactor oversized or multi-domain skills. First determines whether splitting or references/ extraction is appropriate — then executes the correct action. Use when a skill exceeds token thresholds (SK006/SK007) or covers multiple independent domains. Performs candidate assessment before any structural changes; cohesive single-intent skills are redirected to references/ extraction instead of splitting. When splitting is warranted — domain analysis gate, split plan, new SKILL.md generation, validation, and backwards-compatible facade conversion.

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Executes a groomed milestone with parallel kage-bunshin sessions in isolated worktrees. Use when a milestone has been groomed and /groom-milestone has produced a dispatch plan. Reads the dispatch plan, creates an integration branch, spawns one kage-bunshin (independent claude -p process) per wave item in its own worktree — each session is a full orchestrator with the Agent tool. Sequentially merges worktree branches, relays wave discoveries to subsequent waves, then lands the integration branch to main. Takes a milestone number as argument.

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Orchestrator context window discipline enforcement. Prevents the orchestrator from reading source files it will not edit, running diagnostic commands that waste context, and rationalizing delegation bypasses. Use when setting up orchestrator guardrails, reviewing delegation discipline, or diagnosing context window waste in multi-agent workflows. Activates PreToolUse hooks that surface decision points before source file reads and diagnostic command execution.

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Same reverse-thinking method as dh:rt-ica (see dh:rt-ica or dh-glossary for the definition), but localizes any MISSING input to the affected task only, as a non-blocking information-completeness pre-pass before task decomposition and plan generation. Use when grooming backlog items, generating plans, decomposing tasks under uncertainty, or working in brownfield and refactor scenarios. Produces completeness summary (APPROVED-FOR-PLANNING, APPROVED-WITH-GAPS, or BLOCKED-FOR-PLANNING), missing input report with dependency mapping, required unblock actions, and planning annotations for downstream tasks. Use dh:rt-ica instead at the S2 implementation gate where missing inputs must halt execution.

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Use when orchestration or planning agents are producing task plans, task prompts, or TASK.md instructions that must be unambiguous, verifiable, and resistant to hallucination. Applies CLEAR (Concise, Logical, Explicit, Adaptive, Reflective) to structure and write agent task prompts, then adds CoVe (Chain of Verification) checks where accuracy risk is meaningful. Activates on draft task prompts, swarm plans, migration tasks, and multi-step plans requiring independently executable steps.

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Routes to the correct dh skill entry point by intent. Use when unsure which development-harness skill to invoke, starting a development workflow, or invoking /dh directly. Covers capture, groom, plan, execute, single task, quality gates, and milestone routing.

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Reviews browser-rendered HTML, CSS, JSX, TSX, JavaScript, and TypeScript for accessibility, XSS, forms, focus, rendering performance, styles, and lifecycle cleanup. Loaded by dh:code-reviewer when source or framework entrypoints establish frontend execution; composes with TypeScript checks.

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Use when the plan_ref returned by add-new-feature is provided. Executes the SAM implementation loop — opens an attempt per ready task, dispatches each to a specialist agent in parallel, settles and judges what comes back, manages bookend tasks (T0 baseline capture and TN verification), and tracks concerns and contract violations per task. Drives task state through the work ledger via the SAM CLI.

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Execute large-scale automated code transformations safely and idempotently. Use when renaming symbols across a codebase, migrating API call-sites, enforcing new patterns at scale, or applying structural edits to many files at once. Triggers on: 'codemod', 'mass rename', 'migrate all usages', 'transform codebase', 'apply pattern at scale', AST-based refactoring, or any task requiring consistent edits across 10 or more files.

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Use when SAM Stage 5 Execution has completed and task results need independent verification against acceptance criteria. Dispatches a separate reviewer agent to fact-check implementation outputs and returns COMPLETE or NEEDS_WORK with specific findings and remediation tasks.

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SAM-style feature initiation workflow — discovery through codebase analysis, architecture spec, task decomposition, validation, and context manifest. Use when a user asks to add a feature, plan a feature, or convert an idea into an executable SAM plan.

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Transitions a GitHub milestone from planning to active execution. Use when the team is ready to begin a sprint or release cycle — bulk-transitions open issue labels from status:needs-grooming to status:in-progress, updates GitHub Projects V2 Status to In Progress, and confirms before applying changes. Requires milestone number as argument. Use after /group-items-to-milestone.

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Produces a structured, end-to-end linear walkthrough of an unfamiliar codebase by orchestrating parallel subagents across four phases — discovery, tracing, validation, and synthesis. Use when onboarding to a new repository, understanding execution paths from entry points, generating navigable codebase documentation, or needing fact-checked coverage of architecture, deployment, testing, and operations.

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Use this skill when a human needs to review a Deepline Play result and hand feedback, labels, or approval back to the agent for revision, evaluation, comparison, or bounded iteration. Triggers on “put this run in a Sheet,” “review these results,” “read my feedback,” “make this a standing rule,” “never regress on this case,” “compare these runs,” “keep improving,” or “add the revised run to the same spreadsheet.” Skip ordinary Play authoring or execution with no human review loop, generic spreadsheet work, and one-off CSV export.

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Design, create, inspect, update, attach, detach, preview, execute, and verify reusable Vapi Structured Outputs through public API or Server SDK workflows. Use for post-call extraction, typed call artifacts, AI-versus-regex extraction, JSON Schema design, backfilling existing calls, or retrieving structured results programmatically.

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Plans a research project as a decision map that persists across sessions, resolving one ticket per session until the design is defensible and pre-registerable. The map lives as Markdown in the repository, literature sweeps run as parallel research tickets, and the resolved map compiles into a pre-analysis plan. Use at project start, when a design has more open decisions than one conversation can hold, or when planning restarts each session. Not for executing analyses or writing the paper.

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