shipshitdev
OrganizationClaude, Cursor, Codex skills and commands
Categories
Indexed Skills (49)
agent-dispatch
Single front door for agent/subagent architecture, config, and setup. Parses a subcommand — audit, config, init, or route — and routes to the right engine: agent-architecture-audit (diagnose LLM wrapper and agent failures), agent-config-audit (audit and sync AI agent config files across workspaces), agent-folder-init (add or repair .agents/ project context for a repo), or setup-agent-routing (write a machine-readable routing block in CLAUDE.md/AGENTS.md). Backs the /agent command. Use when asked to audit an agent system, check config drift, initialize agent docs, or wire up routing, and the action must be picked from an argument like "audit", "config", "init", or "route".
codex-image-gen
Generate raster images (icons, illustrations, textures, app icons) from a text prompt by driving the Codex CLI's image tool, then extracting the finished PNG from the Codex session rollout. Use when an agent needs a real generated image and has no native image-generation tool. Requires the `codex` CLI, logged in.
comment-mode
Granular feedback on drafts without rewriting. Generates highlighted HTML with click-to-reveal inline comments. Use when user says "comment on this", "leave comments on", "give feedback on", or asks for feedback on a draft. Supports multiple lenses—editor feedback, POV simulation ("as brian would react"), or focused angles ("word choice only", "weak arguments"). A granular alternative to rewrites that lets users review feedback incrementally without losing their voice.
mcp-builder
Creates MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Activates on: "build an MCP server", "create MCP tools", "integrate API via MCP", "write a FastMCP server", "add an MCP server to an agent", or any request to wrap an external API as LLM-callable tools in Python or Node/TypeScript.
nestjs-expert
NestJS architecture, modules, DI, guards, interceptors, pipes, MongoDB/Mongoose integration, auth, and production patterns. Use when building NestJS APIs, designing module structure, implementing auth, handling errors, writing DTOs, or debugging NestJS-specific issues.
ask-dev-loop
Ask which Dev Loop skill or flow fits the current situation. A router over the flagship idea-to-ship path.
feature-intake
Capture a client or stakeholder feature request, turn it into a planner-ready PRD epic with scoped sub-issues, check for duplicate work, and place approved issues on a GitHub Projects kanban. Use when a user invokes feature intake, asks to turn a rough client requirement into GitHub issues, or wants an idea written as a PRD and pushed to a board.
gh-project-board
Configure GitHub Projects v2 kanban boards with Ship Shit Dev defaults: the Backlog / In Progress / Human Review / Done / Deferred Status columns (the dev-loop board-as-truth model) and P0-P3 Priority. Use when setting up, copying, auditing, or normalizing GitHub project boards.
interview
Repo-grounded discovery interview that produces a handoff brief for PRD writing, feature intake, or planning.
prd-task-creator
Create a well-written PRD, task, or GitHub issue/sub-issue for a feature, bug, or enhancement. Use when planning work, writing GitHub issues, breaking down epics into sub-issues, or creating local task files. Common prompts: create a task, write a PRD, open a GitHub issue, create a sub-issue, plan this feature, write up this bug, break this down into issues, I want to add X, implement Y.
setup-agent-routing
Sets up an `## Agent skills` routing block in CLAUDE.md/AGENTS.md plus docs/agents/ so the dev-loop skills (executing-plans, feature-intake, prd-writer, qa-reviewer) know this repo's GitHub issue tracker, kanban label vocabulary, and domain doc layout. Run once per repo before first use of the loop, or when those skills appear to lack tracker, label, or domain context.
agent-config-audit
Audit AI agent instruction files (AGENTS.override.md, AGENTS.md, configured fallbacks, CLAUDE.md, hooks, and settings) across workspaces in read-only report mode. Use when agent configs drift, rules duplicate, files go stale, or after workspace restructuring; apply fixes only when explicitly requested.
code-review
Correctness, security, and spec-fidelity gate for incoming pull requests. Auto-invoked when reviewing a diff, evaluating a PR, running /code-review at any effort level, or asked "is this safe to merge?" Covers bugs, TypeScript hygiene, security, database safety, test existence, devex regressions, feature-flag leaks, and whether the diff matches the originating issue/spec. Multi-PR report-only review routes through review-dispatch; non-serial queue draining is exposed only through exact /merge force.
codebase-advisor
Survey any codebase as a senior advisor and produce prioritized, self-contained implementation plans for OTHER models/agents to execute. Strictly read-only on source code — never implements, fixes, or refactors anything itself. Use when asked to audit a codebase, find improvement opportunities (bugs, security, performance, test coverage, tech debt, migrations, DX), suggest features or where to take the project next (roadmap, product direction), or generate handoff plans for another agent to implement. Does NOT edit code directly — it declines and hands off a plan instead.
wait-what
Re-pitch the last message in plain English using the project's CONTEXT.md vocabulary.
skill-auditor
Audit the skills library for duplicates, stale content, spec violations, and structural issues. Run periodically or before releases.
skill-validator
Validate SKILL.md files against the Agent Skills spec and Claude Code extensions. Run on new or modified skills before committing.
advanced-evaluation
Design and operate LLM-as-a-Judge evaluation systems using direct scoring, pairwise comparison, rubric calibration, evaluator bias mitigation, confidence scoring, and automated quality assessment. Use when building LLM-as-judge systems, comparing model responses, calibrating rubrics, debugging inconsistent evaluations, or designing A/B tests for prompt or model changes.
agent-browser
Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
context-degradation
Recognize, diagnose, and mitigate patterns of context degradation in agent systems. Use when context grows large, agent performance degrades unexpectedly, or debugging agent failures.
context-fundamentals
Explain or reason about foundational context engineering concepts: what context is, the anatomy of a context window, attention mechanics, the U-shaped attention curve, why context quality matters more than quantity, and the mental models needed to interpret context-engineering decisions. Use for conceptual explanation, onboarding, and background reading. Route operational work to context-degradation for attention failures and context-optimization for token-efficiency work.
evaluation
Build evaluation frameworks for agent systems. Use when testing agent performance, validating context engineering choices, or measuring improvements over time.
memory-systems
Design and implement memory architectures for agent systems that persist state across sessions, maintain entity consistency, and reason over structured knowledge. Use when building agents that persist knowledge across sessions, choosing between memory frameworks, maintaining entity consistency, or designing memory architectures for production.
multi-agent-patterns
Design multi-agent architectures for complex tasks. Use when single-agent context limits are exceeded, when tasks decompose naturally into subtasks, or when specializing agents improves quality.
prompt-engineering
Expert guide on prompt engineering patterns, best practices, and optimization techniques. Use when user wants to improve prompts, learn prompting strategies, debug agent behavior, or design content generation prompts.
skill-creator
Guide for creating effective skills. Use when creating a new skill or updating an existing one to extend agent capabilities with specialized knowledge, workflows, or tool integrations.
spec-first
Enforces a spec → plan → execute → verify loop before writing code, preventing "looks right" failures. Activates on "build X", "implement...", "add a feature that...", or any multi-file/unclear-requirements request. Creates spec.md, todo.md, and decisions.md as durable artifacts.
tool-design
Design tools that agents can use effectively, including when to reduce tool complexity. Use when creating, optimizing, or reducing the set of tools available to an agent.
error-handling-expert
Expert in error handling patterns, exception management, error responses, logging, and error recovery strategies for React, Next.js, and NestJS applications. Use when implementing error handling, exception filters, error responses, error logging, or recovery strategies.
graphql-architect
Design and review GraphQL schemas, resolvers, mutations, pagination, and data-loading patterns. Use when building or refactoring GraphQL APIs, adding fields, fixing resolver design, or improving GraphQL performance and safety.
incremental-fetch
Guides construction of resilient data ingestion pipelines from paginated APIs. Activates on: "ingest data from API", "pull tweets", "fetch historical data", "sync from X", "build a data pipeline", "fetch without re-downloading", "resume the download", "backfill older data". NOT for: simple one-shot API calls, websocket/streaming connections, file downloads, or APIs without pagination.
turborepo
Turborepo monorepo build system guidance. Triggers on: `turbo.json`, task pipelines, `dependsOn`, caching, remote cache, the `turbo` CLI, `--filter`, `--affected`, CI optimization, environment variables, internal packages, monorepo structure, and package boundaries. Use when the user configures tasks or workflows, creates packages, sets up a monorepo, shares code between apps, runs changed packages, debugs cache behavior, or works in an `apps/` plus `packages/` workspace.
typescript-expert
Resolves TypeScript and JavaScript problems across type-level programming, performance, monorepo management, migration, and modern tooling. Invoke when diagnosing "type instantiation excessively deep" errors, migrating JS to TS, configuring strict tsconfig, debugging module resolution, or choosing between Biome/ESLint/Turborepo/Nx.
typescript-refactor
TypeScript refactoring and modernization guidelines from a principal specialist perspective. This skill should be used when refactoring, reviewing, or modernizing TypeScript code to ensure type safety, compiler performance, and idiomatic patterns. Triggers on tasks involving TypeScript type architecture, narrowing, generics, error handling, or migration to modern TypeScript features.
domain-modeling
Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a CONTEXT.md, or recording or editing an ADR.
executing-plans
Orchestrate autonomous AI development with task-based workflow and QA gates. Use when implementing a development plan, picking tasks from a queue, or running multi-platform parallel execution with QA gates.
grilling
Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, asks to be grilled, or another skill needs the interview primitive.
prd-writer
Drafts, scopes, and formalizes features as PRDs — a planning agent can consume the output in one shot without re-elicitation. Triggers on "write a PRD for X", "let's plan X", "scope this out", "what should X do", or when a tracker issue needs to be fleshed out before planning. Do NOT use for code edits, debugging, or PR reviews.
qa-reviewer
Runs a structured multi-phase verification pass on completed AI agent work — catching bugs, missed requirements, and incorrect assumptions before changes are committed. Triggers on: "check your work", "review this", after complex multi-step implementations, before committing major refactors, or proactively after any task longer than five steps.
writing-plans
Turn a spec or requirements doc into a comprehensive, bite-sized implementation plan: map every file, define 2-5 minute TDD tasks with complete code, and enforce DRY/YAGNI/frequent-commits discipline. Use when you have requirements ready and need a concrete execution plan before touching code, when a feature spans multiple files and needs decomposition, or when you want agentic workers to execute tasks reliably without guessing.
agent-architecture-audit
Audit LLM and agent applications for wrapper regressions, prompt or memory contamination, tool discipline failures, hidden repair loops, and output rendering corruption. Use before shipping agent features or when an agent works in a direct model call but fails inside the product.
ai-agent-cost-optimizer
Audit and reduce AI agent token and inference spend through context discipline, prompt caching, model routing, batching, and workflow capture. Use when discussing AI coding bills, token waste, model selection, prompt caching, or agent cost optimization.
ai-regression-testing
Design regression tests for AI-assisted development by targeting model blind spots such as sandbox versus production path drift, response-shape mismatches, untested bug fixes, and same-model review failures. Use after AI-generated code changes, bug fixes, API edits, or feature-flag/sandbox changes.
changelog-generator
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation. Use when preparing release notes, summarizing product updates, or turning git commits into customer-facing changelog entries.
readme-sync
Regenerate catalog counts, layout claims, and README summaries from canonical sources. Run after adding, removing, or renaming skills, commands, or bundles.
context-engineering
Supplementary context protocol for agents executing in a repo that has a CLAUDE.md / AGENTS.md (or equivalent config). Use to make an execution agent read project conventions first, treat inputs by trust level, surface plan-vs-convention conflicts instead of silently picking a side, and reuse existing patterns before writing new code.
api-design-expert
Expert in RESTful API design, OpenAPI/Swagger documentation, versioning, error handling, and API best practices for NestJS applications. Use when designing API endpoints, building RESTful APIs, writing OpenAPI/Swagger docs, implementing versioning, or designing error responses and DTOs.
prd-quality-gate
PRD completeness validation. Use to check that a PRD (or issue body that serves as one) contains the required sections before it is handed to a planning/execution agent, so the plan is built from a complete spec instead of hallucinated scope. Run it as a blocking gate or a warning-only lint.
analyze-codebase
Generate comprehensive codebase analysis covering architecture, security, performance, and code quality. Use when user says 'analyze codebase', 'code audit', 'architecture review', or 'project health check'.
Bio shown is the top-scored skill's repo description as a fallback — real GitHub bios land in a future update.