32 skills (repositories by Gentleman-Programming) · sorted by popularity
Prepare Gentle AI changes for review by linking approved issues, following branch and commit naming rules, and drafting pull requests with observed test results. Check change size and required automated checks before claiming readiness.
Coordinate temporary agents for code exploration, independent implementation tasks, verification, reviews, or complex debugging. Define self-contained assignments, run independent work in parallel, and check returned evidence before combining the results.
Prepare and manage GitHub bug reports and feature requests using repository evidence and required forms. Check for duplicates, identify missing information, and verify published issues or comments before reporting the result.
Run two independent reviewers against the same fixed target, then compare their findings. With approval, address severe issues confirmed by both and reassess the fixes, using at most two correction rounds before a final verdict.
Turn reusable workflows and project conventions into concise instructions for AI agents. Structure SKILL.md with required metadata, move supporting material into local files, and register project skills in AGENTS.md when applicable.
Draft clear, considerate comments for code reviews, issue replies, and team updates. Put the actionable point first, explain technical reasons when needed, and give a concrete next step while matching the conversation’s language.
Audit groups of bug reports to find shared root causes, checking claims against current code and tests. Produce a cause map, prioritize fixes that remove faulty mechanisms, and document which issues have enough evidence to close.
Split large code changes into linked pull requests, each with a focused scope. Organize their order, dependencies, and verification steps so reviewers can assess one unit of work at a time.
Structure guides, READMEs, design documents, and pull request descriptions so readers can find answers quickly. Put outcomes first, introduce details gradually, and use examples, tables, and checklists to support understanding and review.
Guide an approved defect fix from reproduction on current main through testing and independent validation. Record evidence for each operator workflow, track change size and rollback scope, and apply review records when receipt-driven development is enabled.
Group bug reports by their underlying cause and plan shared fixes. This skill guides reproduction, checks for unnecessary complexity, and requires named test evidence before treating related issues as resolved.
Audit existing SKILL.md files for clear activation conditions, usable instructions, and defined outputs. Get prioritized findings and specific improvements, with changes applied only when requested and the author's intent preserved.
Build and refresh an index of available skills, including when to use each one and its exact file path. Resolve duplicate entries and give agents a current reference after skills are added, removed, moved, or renamed.
Guide changes to RDD reviewer integrations through a shared Go contract, a common set of processing rules. Define adapter boundaries, validate result handling, and check that runtime migrations preserve existing review outcomes.
Create and verify gentle-ai journeys, which are scripted sequences of product actions. Check their declarations separately from actual execution, review outdated expectations after behavior changes, and record execution results for pull requests.
Prepare external contributions to gentle-ai through approved issues, accurate pull request descriptions, and plans for splitting large changes. Check claims against test results and GitHub state while respecting contributor and maintainer permissions.
Plan commits around complete features, fixes, or documentation changes, keeping related tests and docs together. Split larger work into reviewable units with recorded verification results and clear boundaries for rolling back changes.
Prepare pull requests by checking approved issue links, change-type labels, and required automated checks. Draft the repository’s PR template using observed test results, while leaving commits, pushes, PR creation, and merging under human control.
Split changes exceeding 400 lines into linked pull requests with clear boundaries and dependencies. Choose a chain structure, keep tests and documentation with each work unit, and document review order, verification plans, and justified size exceptions.
Write and review Go tests using patterns suited to functions, file operations, and terminal interfaces. Cover multiple scenarios, check state changes, and compare rendered output with saved expected results while keeping slow integration tests separately skippable.
Write warm, direct collaboration comments. Trigger: PR feedback, issue replies, reviews, Slack messages, or GitHub comments.
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Create Gentle AI pull requests with issue-first checks. Trigger: creating, opening, or preparing PRs for review.
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Trigger: RDD, receipt-driven development, review authority, receipt/lineage, correction/recovery, delivery gate/kill switch, bounded review defects. Guide work.
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Plan commits as reviewable work units. Trigger: implementation, commit splitting, chained PRs, or keeping tests and docs with code.
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