「codebase」の検索結果

Build an animation from scratch, making the decisions in the order that determines whether it feels right — should it animate at all, what purpose, which tool, which properties, which curve and duration, how it interrupts, how it exits. Writes the implementation. Use when asked to animate something, add motion, make a component feel alive, or build a transition. For critiquing existing motion use review-animations; for auditing a whole codebase use improve-animations.

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。

Write Stripe code against what the API does today — plan the product shape, confirm every parameter from Stripe's own docs and schemas, and keep the agent in a sandbox. Use when adding checkout, billing, subscriptions, invoicing, or webhooks to a codebase, or when debugging Stripe integration code that compiles but behaves wrong.

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。

Critique and improve the visual design of an existing UI component with concrete implementation guidance. Use when the user asks to redesign, restyle, reimagine, polish, or improve a component, screen, or interface, especially in React and Tailwind codebases.

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。

Compiles any research input — PDF papers, GitHub repositories, experiment logs, code directories, or raw notes — into a complete Agent-Native Research Artifact (ARA) with cognitive layer (claims, concepts, heuristics), physical layer (configs, code stubs), exploration graph, and grounded evidence. Use when ingesting a paper or codebase into a structured, machine-executable knowledge package, building an ARA from scratch, or converting research outputs into a falsifiable, agent-traversable form.

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。

Designs incremental migration strategies, identifies service boundaries, produces dependency maps and migration roadmaps, and generates API facade designs for aging codebases. Use when modernizing legacy systems, implementing strangler fig pattern or branch by abstraction, decomposing monoliths, upgrading frameworks or languages, or reducing technical debt without disrupting business operations.

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。

Audit a codebase or directory for security issues (hardcoded secrets, injection, unsafe deserialization, weak crypto, authz gaps) and produce a structured findings report. Use when the user asks for a security review, an audit, or to check code for vulnerabilities. Report only — never fix.

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。

Generate or update project documentation verified against the codebase

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。

codebase intel | map graphify docs learnings mempalace

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。

Guide existing codebase onboarding through mapping, doc ingest, and planning setup

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。

Deep file-focused code review for correctness bugs. Unlike shallow-review which runs 6 specialists in parallel across the entire patch, deep-review focuses on user-specified files with full pattern catalogs (500+ patterns), codebase investigation, and source-level context gathering. Use when: the user specifies particular files for focused review, a shallow review flagged areas that need deeper investigation, reviewing critical-path code changes, examining complex serialization/lifecycle/state-machine changes. The user instructs which files to focus on (typically a subset of files in the patch).

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。

Findings-driven targeted code review. Understands the patch via patch-explainer and surrounding code via codebase-analysis, then consults a catalog of bug patterns (~11 categories under references/categories/). Picks only categories whose diff-signals match the patch and items whose "look for" hints match actual code shapes, groups them by review focus (function/file/feature), and spawns parallel subagents — each with a tight scope and selective checklist. Use for medium-to-large patches (50-1000 LOC) as a focused alternative to whole-patch ensemble or whole-file deep review. Triggers on: "review this patch/diff/change", "find bugs in this change", "scoped review", "what could go wrong here", "review using findings", or proactive PR 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。

Shallow (quick) ensemble bug-finding review using 6 specialist agents in parallel. Each specialist reviews the same patch through a different lens: Logic & Types, Boundaries & I/O, Concurrency & State, Resources & Serialization, Absence Analysis, and API Completeness. Findings are merged and deduplicated. Best for: quick first-pass review of patches, triage of diffs, broad surface-level bug scan. For deeper file-focused review with full pattern catalogs and codebase investigation, use the deep-review skill instead.

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。

Turn an idea or objective into a goal package for /goal. Interviews the user, builds a reviewed fact sheet via Plannotator, then explores the codebase to produce an execution plan.

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。

Add regression test cases to the Bifrost provider harness (the Postman collection run via `make run-provider-harness-test`) based on a merged PR or a GitHub issue. Fetches the PR/issue, traces the affected wire path in the codebase, checks existing harness coverage, designs cases following harness conventions, inserts them into tests/e2e/api/collections/provider-harness.json without reformatting the file, and validates via the augment and filter scripts. Invoked with /harness-test-writer <PR# | issue# | URL> or /harness-test-writer (prompts for a reference).

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。

Write, update, and review Mintlify MDX documentation for Bifrost features. Explores the full codebase (UI, Go backend, config schema), validates config.json examples, places screenshot placeholders, and presents outlines for approval before writing. Invoked with /docs-writer <feature-name>, /docs-writer update <doc-path>, or /docs-writer review <doc-path>.

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。

Investigate a GitHub issue by fetching details, analyzing the codebase, researching documentation, and presenting an actionable implementation plan with test guidance. Use when asked to investigate, analyze, triage, or plan work for a GitHub issue. Invoked with /investigate-issue <ISSUE_ID> or /investigate-issue (prompts for ID).

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。

Read-only code quality audit — scan the current working directory for common issues (bugs, dead code, security hotspots, missing error handling) and return a prioritised findings report. No files are edited. Use when asked to "audit the code", "quick audit", "find issues", "code scan", or "what's wrong with this codebase". (munder-difflin)

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。

Extract a comprehensive design system (DESIGN.md) directly from frontend source code — React, Vue, Svelte, Angular, plain HTML/CSS, or any web framework. Analyzes component files, stylesheets, Tailwind configs, theme definitions, and design tokens to produce a rich, Stitch-compatible design system document. Use this skill whenever the user wants to reverse-engineer a design system from an existing codebase, audit the visual language of a project, extract design tokens from source files, or understand the styling patterns in a frontend repo — even if they just say "what does this app look like?" or "pull out the design from this code."

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。

Systematic workflow for auditing TypeScript codebases for import hygiene issues (value vs. type imports, duplicates), missing base class extensions, and incomplete barrel file re-exports, with actionable fix patterns.

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。

Ensure codebase deliverables are properly packaged as ZIP exports in a dedicated final step

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。

Ensures codebase deliverables are properly exported as ZIP archives through a dedicated finalization step

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。

Ensures codebase deliverables are properly archived into a ZIP file before marking task complete

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。

Sets up and runs AFL++ for multi-core fuzzing of C/C++ projects built with afl-clang-fast or afl-gcc-fast. Covers instrumentation modes, parallel main and secondary campaigns, persistent mode, corpus minimization, and crash triage. Use when scaling fuzzing across cores, fuzzing a mature C/C++ codebase, reading the afl-fuzz status screen, or moving on after libFuzzer has plateaued.

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。

Graph-informed mutation testing triage. Parses codebases with Trailmark, runs mutation testing and necessist, then uses survived mutants, unnecessary test statements, and call graph data to identify false positives, missing test coverage, and fuzzing targets. Use when triaging survived mutants, analyzing mutation testing results, identifying test gaps, finding fuzzing targets from weak tests, running mutation frameworks (including circomvent and cairo-mutants), or using necessist.

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。