Create short HTML lessons and interactive practice tailored to learning goals and prior progress. Keep learning records, trusted resources, and quick reference materials so study can continue across sessions with exercises designed for long-term retention.
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Write and revise documents that guide AI agents, including skills and AGENTS.md files. Organize steps, define checkable completion criteria, and clarify when to load references so agents can follow a consistent process across different tasks.
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Set up dependency-cruiser in a TypeScript repository to enforce package boundaries: outside code uses public entry files while implementation stays in subfolders. Add checks, a starter package, and documentation, then verify that forbidden imports fail.
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Summarize the current conversation into a handoff document so another agent can continue the work. Reference existing artifacts, suggest skills for the next session, remove sensitive information, and save the document in the operating system’s temporary directory.
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Draft or revise pull request descriptions that show the change, evidence of its behavior, and merge risks. Use concise diagrams, trees, or diffs alongside before-and-after results to help reviewers assess impact and how easily changes can be reversed.
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Diagnose difficult bugs and performance regressions by first building a repeatable check for the exact symptom. Minimize the reproduction, test ranked hypotheses, apply a fix, and verify the original scenario with regression tests where suitable.
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Create an interactive bash script that guides people through manual setup or migration tasks. It opens relevant pages, explains each action, collects values, and saves settings to .env files or GitHub secrets with confirmation steps.
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Turn an existing conversation and codebase context into a feature specification. Organize user needs, implementation decisions, testing plans, and scope, then publish the specification to the project’s issue tracker with a label marking it ready for agent work.
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Turn a specification and its linked tickets into code. Multiple agents work on available tasks in separate worktrees, combine changes on one integration branch, and complete a code review before preparing the result for review or closing tickets.
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Research a question using original sources such as official documentation, source code, and specifications. A background agent records findings with sources for each claim and saves a Markdown note following the repository’s existing conventions.
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Review a codebase for design friction and compare refactoring candidates in an HTML report with before-and-after diagrams. Then explore a chosen candidate through questions about constraints, module design, and testing.
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Turn a large, unclear idea into a shared map of decisions in an issue tracker. Record answers, dependencies, and unresolved questions across sessions until the route to a defined goal is clear enough to hand off.
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Review a coding session to identify improvements to the agent’s working environment. Get prioritized suggestions for finding files, strengthening automated checks, clarifying guidance, reducing costly tool calls, and accessing missing information.
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Refine a plan or design through an ongoing interview while creating documentation. The skill combines grilling and domain-modeling to produce architectural decision records, which capture design decisions, and a glossary of relevant terms.
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Implement work described in a specification or set of tickets, using test-first development where agreed. Run type checks and tests throughout, review the completed changes, and commit the work to the current branch.
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Migrate TypeScript test data from type assertions to @total-typescript/shoehorn helpers. Use partial objects for focused tests and deliberately invalid data for error cases, then check that the migrated tests pass type checking.
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Explore a writing topic through ongoing questions and collect sentences, experiences, metaphors, and unfinished thoughts in one Markdown file. Build a pool of usable material without committing to an outline or article structure.
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Find the right skill and sequence for your current development task, from shaping an idea to implementation, debugging, and review. The guide also explains when to prototype, prepare specifications, or move work into a fresh session.
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Review issues and external pull requests, classify them, verify their claims, and assign a handling state. The skill checks existing implementations and past rejections, requests missing details, and prepares briefs that agents or human maintainers can act on.
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Turn existing Markdown material into an article by choosing among suggested next passages. Establish what readers already know, introduce concepts before relying on them, and build the article one selected passage at a time.
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Shape Markdown notes, fragments, or transcripts into a separate article through a collaborative drafting session. Choose an opening, establish what readers already know, and develop each paragraph or block in an order that introduces concepts before relying on them.
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Build a disposable prototype to answer a specific design question. Use a shareable HTML demo to explore logic and state changes, or compare distinct UI variations on one route, then record the decision and retain the prototype separately.
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Set up the repository settings that engineering skills read: where work is tracked, which triage labels to use, and where domain documents belong. Review existing files and confirm drafts before writing configuration documents.
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Build features or fix bugs by writing one failing test, then the minimum code needed to pass it. Test agreed public interfaces, the boundaries callers use, to check behavior without depending on internal implementation details.
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