「codebase」の検索結果

Audit Go nolint directives for staleness and lazy justifications. Mechanically verifies each suppression with golangci-lint, then runs adversarial Red/Blue/White debates on the top candidates for removal. Use when inheriting a Go codebase, during periodic cleanup, or when nolint count is growing unchecked.

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Comprehensive security audit covering OWASP Top 10, secrets detection, supply chain security, threat modeling, and language-specific vulnerability patterns. Investigates actual code paths rather than grep-matching keywords. Generates a scored SECURITY_AUDIT.md with prioritized remediation. Use when assessing application security, preparing for a security review, or onboarding to a codebase with security concerns.

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Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.

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Get productive with agentic coding assistants — task framing, iterative prompting, file-scoped workflows, review loops, and multi-file refactors. Use when pairing with an AI coding agent on real codebases.

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Ship iOS/Android apps with Capacitor: web codebase, native plugins, live updates, and store builds. Use when wrapping a web app as native mobile apps.

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Audit codebases for leaked secrets and hardcoded credentials, generate .env templates, configure secrets management with AWS Secrets Manager, Vault, Doppler, or GCP Secret Manager, set up credential rotation, and integrate secrets into CI/CD pipelines via OIDC federation

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Generate OpenAPI 3.1 documentation from your API codebase. Auto-detects Express, Fastify, NestJS, Django, FastAPI, Flask, Rails, Spring, Go, and more. Triggers: you need API documentation, OpenAPI spec, Swagger docs, endpoint reference, or REST API docs.

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Generate Mermaid architecture diagrams from your codebase. Produces C4 context and container diagrams, sequence diagrams for key flows, ER diagrams from database schemas, and module dependency graphs. Use when you need architecture diagrams, system diagrams, database ERD, sequence diagrams, dependency visualization, or C4 model diagrams.

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Generate Excalidraw architecture diagrams (.excalidraw JSON files) from your codebase. Triggers: you need whiteboard-style sketches that read as a thinking artifact rather than a polished spec — ideal for design.

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Run a focused tech debt reduction sprint — inventories all technical debt (TODOs, outdated deps, missing tests, god objects), fixes code smells, removes dead code, then hardens with a review pass. Use when a codebase feels sluggish, before a major feature push, or on a regular maintenance cadence.

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Inventory and prioritize all technical debt in a codebase. Scans for TODO/FIXME/HACK markers and stale comments, outdated and deprecated dependencies with CVE detection, high-churn files and cyclomatic complexity hotspots, duplicated code blocks.

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Prepare for fundraising due diligence — runs CTO, CFO, CPO, sales, and codebase health reviews to produce a consolidated investor brief with scorecard, red flags, and strengths. Use before Series A, seed round, acqui-hire evaluation, or board presentation.

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Deep codebase cleanup — kills dead code, fixes all lint/format warnings, removes orphaned files, cleans stale TODOs, strips security hazards, tightens TypeScript strict mode, and organizes imports. Triggers: clean up, dead code, unused imports, lint, technical debt cleanup.

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Audit a codebase for product-market fit readiness -- evaluate startup PMF signals, core value loop tightness, feature scatter vs focus ratio, user activation funnel friction, retention hook infrastructure, pricing flexibility, analytics event coverage, CI/CD iteration speed, and growth-stage maturity for pre-seed through Series A products.

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Audit a product codebase for growth readiness using the AARRR pirate metrics framework. Triggers: launching a new product, diagnosing low conversion, or planning a growth sprint.

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Audit a healthcare software codebase for HIPAA Privacy and Security Rule compliance, HITECH breach notification readiness, 21st Century Cures Act interoperability requirements, and state-level regulatory gaps..

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Whole-codebase analysis powered by Gemini 2.5 Pro's 2M token context window. Triggers: bounded per-module analysis misses inter-module patterns or when you need a full-graph view before a major refactor.

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Maps the entire API surface of a codebase -- route definitions, middleware chains, auth requirements, request/response types, deprecated endpoints, orphaned endpoints, and cross-endpoint inconsistencies..

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Audit contract management codebases for clause extraction accuracy, obligation tracking completeness, risk scoring model quality, renewal management, SLA monitoring, liability exposure, force majeure handling, and IP assignment detection..

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Analyzes infrastructure costs at 1K-100K user scales by reading the actual codebase, auto-detecting cloud providers, modeling per-action costs, and projecting total monthly spend with optimization recommendations.

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Deep cross-layer consistency audit for any codebase. Traces every feature from UI to database, finds broken wiring, missing handlers, model mismatches, and security gaps. Auto-fixes critical and warning issues. Use this after building features, before releases, or whenever something feels off. Works with any tech stack.

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Allocate testing effort based on risk and failure likelihood using Google's SET/SWE/TE model. Use when user says "risk-based testing", "where should I focus testing", "test coverage strategy", "prioritize what to test", "high risk areas", or needs to decide how to distribute QA effort across a codebase - even if they don't explicitly say "risk-based".

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Document and prioritize technical debt. Use when the user says "tech debt", "legacy code", "this code is a mess", "refactoring plan", "we need to clean this up", "paying down debt", "this is hard to change", "how do we fix this codebase", or has code that's difficult to understand or modify - even if they don't explicitly say "technical debt".

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Audit a repo's agent context — CLAUDE.md files, codebase docs, skills, and tool/MCP designs — against Anthropic's Claude 5 context-engineering guidance ("unhobbling": Anthropic cut ~80% of Claude Code's system prompt with no eval loss). Finds overconstraint, conflicting instructions, redundancy, stale facts, and missing "unknown knowns"; produces a scored findings report with concrete rewrites, then applies approved fixes. Use when someone says "audit my CLAUDE.md", "context audit", "unhobble this repo", "review our agent docs/skills/tools", or after upgrading to Claude 5-generation models.

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。