203 skills · sorted by relevance
Explore ideas and working methods through focused conversation, one question at a time. Identify recurring patterns, surprising contradictions, and distinctive approaches, then turn discoveries into named concepts and a documented session summary.
Verify code changes before committing or shipping by running tests, builds, and checks against requirements. Use fresh command output to support completion reports, confirm bug fixes, and check work reported by other agents.
Turn a multi-step feature into an implementation plan that another engineer can follow without prior context. The plan includes exact file paths, complete code, test commands, expected results, and small, verifiable steps.
Organize multi-step work into tasks, track dependencies and status, and save progress checkpoints. Record completed work, unfinished steps, and decision context so an agent can review the saved state and continue in a later session.
Develop behavior changes by first observing an expected test failure, then making the smallest passing implementation. Refactor with tests passing, and document preserved behavior and measured runtime whenever tests are consolidated.
Turn an agreed plan into small work tickets, each covering a complete, testable feature across the necessary layers. Identify dependencies and available starting points so people or future agent sessions can pick up clearly bounded work.
Examine an existing plan, decision, or design through one question at a time, each with a suggested answer. Clarify assumptions, contradictions, and dependencies, then summarize agreed decisions, needed changes, and unresolved blockers.
Test one risky assumption through a prototype with an agreed deadline, hypothesis, and success signal. Record observations and the source revision, then return a keep, discard, or inconclusive verdict with the status of each artifact.
Run repeated rounds of code fixes, performance improvements, or other refinements with defined goals and progress tracking. Evaluate each round, stop when appropriate, and optionally use numeric measurements to keep improvements or roll back regressions.
Review a pull request or feature in two stages: first check implementation against recorded requirements, then examine code quality. Identify unfinished code, logic and security issues, and changes needed before merging in a combined report.
Turn a rough request into a structured AI prompt with a clear goal, output format, and constraints. For complex work, add smaller tasks, separate creator and reviewer roles, and explicit checks for accuracy and uncertainty.
Write or review skills for a consistent process across runs. Check activation conditions, ordered steps, completion criteria, and reference placement, then identify unclear instructions, overlapping triggers, and content that belongs in an existing skill.
Gather advice from multiple language models assigned different roles, then combine their proposals and critiques into a recommendation. Set budget and depth limits while retaining disagreements, minority views, and risks for decisions or implementation planning.
Create a product requirements document for a new feature or product. Clarify users, problems, goals, and constraints, then organize prioritized requirements, acceptance criteria, implementation phases, and risks into a structured document for AI-assisted development.
Compare technical choices through structured discussions among available AI providers. Use independent reviews or rounds of cross-critique to examine risks and trade-offs, then receive a synthesis of agreement, disagreement, recommended decisions, and concrete next steps.
Evaluate feedback from reviewers, CI bots, or other AI agents against the actual code and requirements. Apply valid fixes one at a time, verify each change, and explain disagreements using evidence from callers, tests, or existing conventions.
Restore project files from a previous Git checkpoint after previewing affected files and receiving explicit confirmation. Create a safety tag before restoration, preserve recorded lessons, and keep the current branch and commit history in place.
Finish a development branch by running tests and reviewing changes, then choose whether to create a pull request, merge locally, keep the branch, or discard it. Optional version and changelog updates support release preparation.
Analyze reference articles and social posts to uncover structure, persuasive techniques, and writing patterns. Turn the findings into reusable templates, opening patterns, and interview questions for planning new content.
An early-stage framework for documenting an existing product’s design and architecture. Command parsing, output setup, and metadata generation are implemented; extracting colors, components, APIs, and architecture remains in progress or planned.
Investigate reproducible bugs by recreating symptoms, testing one possible cause at a time, and checking fixes in both a simplified test case and the original scenario. Retry limits keep unsuccessful fixes from continuing unchecked.
Detects whether a task concerns software development or research and strategy by examining the request and project files. Workflow skills can use the result to choose agents, output formats, and review criteria suited to the work.
Audit an application or selected features with a structured checklist. Record evidence for broken behavior, incomplete implementations, and inconsistent patterns, then organize findings by severity and propose a prioritized repair plan.
Compare two to four viable approaches against your requirements and constraints. See each option’s benefits, drawbacks, effort, risk, and ease of reversal, alongside a reasoned recommendation and next steps for the option you choose.