dyad:debug-with-playwright
Debug E2E tests by taking screenshots at key points to visually inspect application state.
dyad:pr-screencast
Record a visual demonstration of the key feature of this PR using screenshots and add it as a new comment to the PR.
dyad:lint
Run pre-commit checks including formatting, linting, and type-checking, and fix any errors.
dyad:pr-rebase
Rebase the current branch on the latest upstream changes, resolve conflicts, and push.
dyad:pr-fix:comments
Read all unresolved GitHub PR comments from trusted authors and address or resolve them appropriately.
dyad:e2e-rebase
Rebase E2E test snapshots based on failed tests from the PR comments.
dyad:deflake-e2e-recent-commits
Automatically gather flaky E2E tests from recent CI runs on the main branch and from recent PRs by wwwillchen/keppo-bot/dyad-assistant, then deflake them.
dyad:promote-beta-to-stable
Promote the latest pre-release to a stable release by creating a release branch, bumping the version, and pushing.
dyad:add-models
Add one or more AI models to the language model constants file, researching specs from official docs.
dyad:fix-issue
Create a plan to fix a GitHub issue, then implement it locally.
dyad:fast-push
Commit any uncommitted changes, run lint checks, fix any issues, and push the current branch. Delegates to a haiku sub-agent for speed.
dyad:multi-pr-review
Multi-agent code review system that spawns three independent Claude sub-agents to review PR diffs. Each agent receives files in different randomized order to reduce ordering bias. One agent focuses specifically on code health and maintainability. Issues are validated using reasoned analysis rather than simple vote counting. Reports merge verdict (YES / NOT SURE / NO). Automatically deduplicates against existing PR comments. Always posts a summary (even if no new issues), with low priority issues in a collapsible section.
code-change-verification
Run the mandatory verification stack when changes affect runtime code, tests, or build/test behavior in the OpenAI Agents Python repository.
examples-auto-run
Run python examples in auto mode with logging, rerun helpers, and background control.
final-release-review
Perform a release-readiness review by locating the previous release tag from remote tags and auditing the diff (e.g., v1.2.3...<commit>) for breaking changes, regressions, improvement opportunities, and risks before releasing openai-agents-python.
test-coverage-improver
Improve test coverage in the OpenAI Agents Python repository: run `make coverage`, inspect coverage artifacts, identify low-coverage files, propose high-impact tests, and confirm with the user before writing tests.
runtime-behavior-probe
Plan and execute runtime-behavior investigations with temporary probe scripts, validation matrices, state controls, and findings-first reports. Use only when the user explicitly invokes this skill to verify actual runtime behavior beyond normal code-level checks, especially to uncover edge cases, undocumented behavior, or common failure modes in local or live integrations. A baseline smoke check is fine as an entry point, but do not stop at happy-path confirmation.
csv-workbench
Analyze CSV files in /mnt/data and return concise numeric summaries.
pr-draft-summary
Create the required PR-ready summary block, branch suggestion, title, and draft description for openai-agents-python. Use in the final handoff after moderate-or-larger changes to runtime code, tests, examples, build/test configuration, or docs with behavior impact; skip only for trivial or conversation-only tasks, repo-meta/doc-only tasks without behavior impact, or when the user explicitly says not to include the PR draft block.
implementation-strategy
Decide how to implement runtime and API changes in openai-agents-python before editing code. Use when a task changes exported APIs, runtime behavior, serialized state, tests, or docs and you need to choose the compatibility boundary, whether shims or migrations are warranted, and when unreleased interfaces can be rewritten directly.
openai-knowledge
Use when working with the OpenAI API (Responses API) or OpenAI platform features (tools, streaming, Realtime API, auth, models, rate limits, MCP) and you need authoritative, up-to-date documentation (schemas, examples, limits, edge cases). Prefer the OpenAI Developer Documentation MCP server tools when available; otherwise guide the user to enable `openaiDeveloperDocs`.
docs-sync
Analyze main branch implementation and configuration to find missing, incorrect, or outdated documentation in docs/. Use when asked to audit doc coverage, sync docs with code, or propose doc updates/structure changes. Only update English docs under docs/** and never touch translated docs under docs/ja, docs/ko, or docs/zh. Provide a report and ask for approval before editing docs.
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screenpipe-health
Check Screenpipe health status, process state, and diagnose common issues
screenpipe-cli
Manage screenpipe pipes (scheduled AI automations) and connections (Telegram, Slack, Discord, etc.) via the CLI. Use when the user asks to create, list, enable, disable, run, or debug pipes, or manage service connections from the command line.
screenpipe-api
Query the user's screen recordings, audio, UI elements, and usage analytics via the local Screenpipe REST API at localhost:3030. Use when the user asks about their screen activity, meetings, apps, productivity, media export, retranscription, or connected services.
release
Release the screenpipe monorepo. Bumps versions, triggers GitHub Actions for app, CLI, MCP, and JS packages.
screenpipe-team
Query the org's screenpipe telemetry as an enterprise admin — devices, members, recent activity, and substring search across the team's screen recordings and audio transcripts. Use when the user asks about their team, a teammate's activity, what their organization worked on, app usage across the org, or anything that requires seeing data beyond the user's own machine. The skill is only installed for enterprise admins; ordinary users won't see it.
render-html-report
Produce a human-facing visual report — a chart, dashboard, scorecard, or styled summary — that renders as a live page in the screenpipe viewer instead of plain text. Use when the task asks for a visual/graphical output rather than a plain note; do NOT use for plain text or raw data (prefer a markdown note for those).
screenpipe-tauri
Add or change Tauri commands and TypeScript bindings in the screenpipe desktop app. Use when editing #[tauri::command] handlers, lib/utils/tauri.ts, or Rust types exported to the frontend.
screenpipe-logs
Retrieve and analyze Screenpipe CLI backend logs and desktop app logs for debugging
react-email
Use when creating HTML email templates with React components - welcome emails, password resets, notifications, order confirmations, newsletters, or transactional emails.
code-quality
General Correctness rules, Rust patterns, comments, avoiding over-engineering. When writing code always take these into account
debugging
How to debug tursodb using Bytecode comparison, logging, ThreadSanitizer, deterministic simulation, and corruption analysis tools
storage-format
SQLite file format, B-trees, pages, cells, overflow, freelist that is used in tursodb
differential-fuzzer
Information about the differential fuzzer tool, how to run it and use it catch bugs in Turso. Always load this skill when running this tool
testing
How to write tests, when to use each type of test, and how to run them. Contains information about conversion of `.test` to `.sqltest`, and how to write `.sqltest` and rust tests
async-io-model
Explanations of common asynchronous patterns used in tursodb. Involves IOResult, state machines, re-entrancy pitfalls, CompletionGroup. Always use these patterns in `core` when doing anything IO
transaction-correctness
How WAL mechanics, checkpointing, concurrency rules, recovery work in tursodb
cdc
Change Data Capture - architecture, entrypoints, bytecode emission, sync engine integration, tests
index-knowledge
Generate hierarchical AGENTS.md knowledge base for a codebase. Creates root + complexity-scored subdirectory documentation.
mvcc
Overview of Experimental MVCC feature - snapshot isolation, versioning, limitations
pr-workflow
General guidelines for Commits, formatting, CI, dependencies, security
qmd
Search markdown knowledge bases, notes, and documentation using QMD. Use when users ask to search notes, find documents, or look up information.
release
Manage releases for this project. Validates changelog, installs git hooks, and cuts releases. Use when user says "/release", "release 1.0.5", "cut a release", or asks about the release process. NOT auto-invoked by the model.
skill-creator
Guide for creating effective skills that extend agent capabilities with specialized knowledge, workflows, or tool integrations. Use this skill when the user asks to: (1) create a new skill, (2) make a skill, (3) build a skill, (4) set up a skill, (5) initialize a skill, (6) scaffold a skill, (7) update or modify an existing skill, (8) validate a skill, (9) learn about skill structure, (10) understand how skills work, or (11) get guidance on skill design patterns. Trigger on phrases like \"create a skill\", \"new skill\", \"make a skill\", \"skill for X\", \"how do I create a skill\", or \"help me build a skill\".
data-visualization
Use for creating publication-quality charts and multi-panel analysis summaries. Triggers when tasks involve visualizing data, plotting results, creating charts, or producing visual reports from analysis output.
web-research
Searches multiple web sources, synthesizes findings, and produces cited research reports using delegated subagents. Use when the user asks to research a topic online, search the web, look something up, find current information, compare options, or produce a research report.
arxiv-search
Searches arXiv for preprints and academic papers, retrieves abstracts, and filters by topic. Use when the user asks to find research papers, search arXiv, look up preprints, find academic articles in physics, math, CS, biology, statistics, or related fields.
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