Development skills for AI coding agents

Skills for software development workflows. Each skill is a packaged set of instructions you install into Cursor, Claude Code, GitHub Copilot, Windsurf or any other supported agent, so the agent follows the same workflow every time.

18 skills in this category.

Skills in Development

  • Your pathfinder for navigating unknown codebases. Investigates with precision, implements surgically, and never assumes — if it doesn't know, it says so. Maintains a .notebook/ knowledge base that grows across sessions, turning every discovery into lasting intelligence. Summons available skills, MCPs, and docs when the mission demands.

  • Behavioral guidelines to reduce common LLM coding mistakes.

  • Expert in Confluence operations using Atlassian MCP.

  • Write, review, and edit documentation files with consistent structure, tone, and technical accuracy.

  • Evaluate a repo agent harness (AGENTS.md, rules, skills, skill refs) for broken paths/commands, redundant instructions, and usefulness using a stack-agnostic dual-judge protocol with planted traps. HIGH PRIORITY questionnaires at top: Q1 optional docs, Q2 B/C budget before Track A (certainty/tokens). A always runs after Q2; B/C opt-in. ADRs/RFCs excluded from T2. Mixed apply uses 11-mixed-apply.md (KEEP/CUT).

  • Manage Jira issues via Atlassian MCP — search, create, update, transition status, and handle sprint tasks. Auto-detects workspace configuration.

  • Specialist in designing and implementing scalable modular monolith architectures using NestJS with DDD, Clean Architecture, and CQRS patterns.

  • Autonomous senior-operator mode for AI agents that resolve tasks end to end without babysitting and never create new problems. The agent verifies every claim against real evidence (web search dated to the current month and year, the codebase, and available tools, MCPs, and CLIs); it never guesses, never fakes confidence, and never claims something is done without proof. It stays silent and keeps working, interrupting the user only on three stops, namely a destructive or irreversible action, a dead-end with no evidence after exhausting sources, or genuine ambiguity that changes the outcome. Output is short, literal, and human.

  • Address review and issue comments on the open GitHub PR for the current branch using gh CLI.

  • Opinionated Rails conventions: rich models, concerns, CRUD-everything, state-as-records, minimal dependencies, Minitest with fixtures. Load this skill BEFORE any code-level thinking, not only before editing a file. It is required the moment a task touches Rails code in ANY way: designing or even just discussing a data model, schema, migration, entity, association, field, validation, class, or method name; writing, planning, reviewing, analyzing, testing, debugging, or refactoring; or proposing any model, table, column, route, or code snippet inline in chat. If you are about to name a model or sketch a column you are already in scope, even in an exploratory back-and-forth where no file is written yet. Do not let a \"we're just discussing\" framing defer it.

  • Senior React Native and Expo engineer for building production-ready cross-platform mobile apps.

  • Complete Shopify development reference covering Liquid templating, OS 2.0 themes, GraphQL APIs, Hydrogen, Functions, and performance optimization (API v2026-01).

  • Scores how completely an implementation fulfills a PRD/spec, case by case, and produces a single comparable final grade. Invoke only when explicitly named (e.g. run spec-driven-eval); do not auto-trigger.

  • Feature planning and implementation with 4 adaptive phases (Specify, Design, Tasks, Execute). Auto-sizes depth by complexity. Writes testable requirements in EARS notation, atomic tasks, atomic Conventional Commits, and requirement traceability. Ships deterministic Python validation scripts so structural gates are enforced by code, not memory. Features an independent Verifier (author != verifier, evidence-or-zero), a discrimination sensor, a decision log (STATE.md), a test-coverage matrix, and a self-improving lessons layer. Stack-agnostic and tool-agnostic.

  • Spec-driven feature work that freezes obligations instead of the plan: one human-reviewed plan with EARS criteria, path, entities, interface and one-way doors, then proof-backed checks, then build, then an independent Verifier.

  • Interviews an unshaped idea into a verdict and a design document with literal decisions for tlc-plan.

  • Implement a work already planned: extracts a checklist, builds it, and proves every check with an independent verifier.

  • Turns decided work — a PRD, design doc, RFC, or thread — into tasks a builder can act on without guessing. Finds slices that each prove something, grounds them in the code, and writes intent, observable criteria with concrete values, the boundary, what the change disturbs, and only the decisions that are hard to reverse. Walks every surface the work exposes and sweeps the nine unwritten requirements, recording each landing as a criterion already in the source, existing behaviour, n/a, or Unresolved — never as a criterion the walk invented. Defaults to one task per source.

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