pytest
TestingCommonly used with
Skills using pytest (705)
skill-finish-branch
Wrap up a branch — run tests, create PR, merge or discard — use when implementation is done
executing-plans
当你有一份书面实现计划需要在单独的会话中执行，并设有审查检查点时使用
finishing-a-development-branch
当实现完成、所有测试通过、需要决定如何集成这份工作时使用
ci-all
Full CI pipeline: run local tests, type check, push branch, and return the pipeline URL. The only command you need before opening a PR.
validate-delivery
Use when user asks to "validate delivery", "check readiness", or "verify completion". Runs tests, build, and requirement checks with pass/fail instructions.
python-quality-gate
Python quality checks: ruff, pytest, mypy, bandit in deterministic order.
ci-tests
Run the test suite for the current repo, auto-detecting Python (pytest/uv), Node (vitest/pnpm), or Rust (cargo test)
verification-loop
This skill should be used when the user asks to "verify code", "run verification", "check quality", "validate changes", or before creating a PR. Provides comprehensive verification including build, type check, lint, tests, security scan, and diff review.
autoresearch-agent
Autonomous experiment loop that optimizes any file by a measurable metric. Inspired by Karpathy's autoresearch. The agent edits a target file, runs a fixed evaluation, keeps improvements (git commit), discards failures (git reset), and loops indefinitely. Use when: user wants to optimize code speed, reduce bundle/image size, improve test pass rate, optimize prompts, improve content quality (headlines, copy, CTR), or run any measurable improvement loop. Requires: a target file, an evaluation command that outputs a metric, and a git repo.
makefile-generation
Generates Makefiles with testing, linting, formatting, and automation targets. Use when starting a project or standardizing build automation.
sharedtech-stack-detection
检测项目技术栈的通用方法，通过分析配置文件识别语言、框架、工具链
execute-feedback
Execute tests on generated code and iterate until passing
js-in-html-testing
Test JS logic embedded in HTML using two-layer strategy - Python unit tests + Playwright browser integration tests
pr-preflight
Full pre-PR merge-readiness check. Run this before opening or merging a pull request — it validates local gates (lint, format, tests), CI status, screenshot evidence, and PR metadata in one pass. Also useful for reviewing an existing PR's readiness.
real-e2e-test
Run real E2E tests against Claude CLI in pytest and tmux modes
translate-i18n
Fill missing i18n translations in the viewer source JSON. Run this after adding or modifying English or Chinese UI strings in claude_tap/viewer_i18n.json — it auto-translates to ja, ko, fr, ar, de, ru via OpenRouter.
plugin-dev-workflow
Guide plugin development workflow — editing skills, agents, hooks, or eval framework in this repo. Use when modifying files in plugins/elixir-phoenix/, lab/eval/, or lab/autoresearch/. Ensures changes pass eval, lint, and tests before committing.
ci
Detect/generate/debug CI pipeline config (GitHub Actions, GitLab CI). Triggers: CI setup, build pipeline, GitHub Actions config, debug CI, GitLab CI.
git-mastery
Advanced Git: rebase, bisect, reflog, cherry-pick, worktrees, LFS. Triggers: rebase, bisect, cherry-pick, reflog, force push, merge conflict, worktree.
coral-debug
Verify and debug changes to CORAL itself — smallest reproduce loop per area (grader / daemon / CLI / hooks / manager / workspace / hub / template / config / web), where to look when something breaks (hung graders, agent restart loops, stalled agents, missing heartbeat actions, corrupted shared state, broken worktree symlinks, grader import errors, wrong-task resume), how to inspect a live or finished run under `.coral/public/`, and the canonical lint/test commands. Use when editing code under `coral/` or chasing a CORAL bug, NOT when adding a new task or extending the framework.
map-debug
Structured MAP debugging via task-decomposer, actor, and monitor agents. Use when reproducing a bug, isolating a regression, or diagnosing an error with specialized agents — including failing or flaky tests (pytest AssertionError), crashes and segmentation faults, memory-corruption or memory errors in native/C extensions, intermittent or load-dependent failures (e.g. 500s under load), data-corruption bugs that only appear in production, scripts or hooks that silently exit or produce no output, and any "find the root cause" / "walk me through diagnosing" / "help me investigate" request. Trigger on phrasing like "failing test", "mysterious error", "segfault", "memory error", "intermittently fails", "root cause", "isolate the cause", "debug why", "diagnose", or "investigate the error". Prefer this over generic investigation when the user wants a systematic decompose-reproduce-fix-verify workflow. Do NOT use for greenfield features; use map-plan or map-efficient.
refactor
基于 Martin Fowler 方法论的系统化代码重构 skill。适用于用户请求重构代码、改进代码结构、减少技术债、清理旧代码、消除 code smell 或提升可维护性时。这个 skill 采用分阶段、带研究与计划的安全增量实施方式。
add-rtk
Install rtk token-compression proxy into agent containers. Routes Bash tool calls through rtk for 60–90% token savings on dev commands (git, cargo, pytest, docker, kubectl, etc.).
omega-memory
Persistent memory for AI coding agents. Teaches agents how to use OMEGA's MCP tools for storing decisions, querying context, coordinating multi-agent workflows, and resuming tasks across sessions.
agent-implementer-sparc-coder
Agent skill for implementer-sparc-coder - invoke with $agent-implementer-sparc-coder
temporal-python-testing
Test Temporal workflows with pytest, time-skipping, and mocking strategies. Covers unit testing, integration testing, replay testing, and local development setup. Use when implementing Temporal workflow tests or debugging test failures.
generate-tests
Generate comprehensive tests for specified code
create-custom-grader
Use when converting an existing benchmark, rubric, verifier, task YAML/JSON, or domain check into SkillEvaluator BYOG/BYOT custom evaluation.
5minbtc
BTC 5分钟K线实时方向预测。v5.8新增: taker_buy主动买量因子(区分主动买/卖) + 订单簿多时刻采样去噪(fetch_depth_avg)。v5.7.3引擎HTTP并行化(4路ThreadPoolExecutor→~3s,原12-18s)。半K线策略——第2分钟执行(progress~40%)，12正交因子含half_body实体延续+momentum/decel冲突降权+V反转+放量突破+Chainlink价格对齐+Platt Scaling+Bull惩罚。ATR乘数x0.55。黑天鹅防护: ATR spike+FNG<25过滤+新闻冲击熔断。v5.7.2冲突裁决: half_body vs imbalance/microprice(已验证2次实盘)+fatigue≥0.8均值回归预警。Binance端点双向故障切换。
finishing-a-development-branch
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work
code-documenter
Generates, formats, and validates technical documentation — including docstrings, OpenAPI/Swagger specs, JSDoc annotations, doc portals, and user guides. Use when adding docstrings to functions or classes, creating API documentation, building documentation sites, or writing tutorials and user guides. Invoke for OpenAPI/Swagger specs, JSDoc, doc portals, getting started guides.
fastapi-expert
Use when building high-performance async Python APIs with FastAPI and Pydantic V2. Invoke to create REST endpoints, define Pydantic models, implement authentication flows, set up async SQLAlchemy database operations, add JWT authentication, build WebSocket endpoints, or generate OpenAPI documentation. Trigger terms: FastAPI, Pydantic, async Python, Python API, REST API Python, SQLAlchemy async, JWT authentication, OpenAPI, Swagger Python.
python-pro
Use when building Python 3.11+ applications requiring type safety, async programming, or robust error handling. Generates type-annotated Python code, configures mypy in strict mode, writes pytest test suites with fixtures and mocking, and validates code with black and ruff. Invoke for type hints, async/await patterns, dataclasses, dependency injection, logging configuration, and structured error handling.
test-python-binding
Build and test the NeMo Relay Python binding and worker plugin SDK; use for python/nemo_relay, python/plugin, or crates/python changes
api-test-suite-builder
Use when the user asks to generate API tests, create integration test suites, test REST endpoints, or build contract tests.
qatest-execution
测试��行方法，包含测试框架检测、测试运行、结果解析
backend
Python server code, APIs, async, strict typing.
harness-audit
Score a project's agent harness across 5 subsystems (Instructions / State / Verification / Scope / Lifecycle), identify the bottleneck, and produce a prioritized improvement plan. Use when assessing if a project is ready to graduate to [LONG-RUN] status, when an agent keeps failing despite good models, or when adopting our stack on a new codebase. Do NOT use to design or build a new harness from scratch — this only scores an existing one; for greenfield harness/agent architecture use harness-design (or agent-harness-design).
source-command-methodology-advisor
Analyzes your codebase and asks 3 targeted questions to recommend the right AI-assisted development methodology stack
check-and-test
Run lint checks (ruff for Python, Biome for TS/JS), type checks (pyright for Python, tsc for TS/JS), and the standard pytest tiers (unit + e2e + tests skipped during pre-commit). Investigates failures to determine if they are application bugs or test issues, and fixes application bugs rather than weakening tests. Does not run paid-LLM real-API tests or scenario probes from the test-* command family.
e2e-test
Run claude-tap end-to-end tests with pytest
ship
Build, commit, push & version bump workflow - automates the complete release cycle
qa
Test writing - pytest suites, edge cases, regressions.
harness-audit
Score a project's agent harness across 5 subsystems (Instructions / State / Verification / Scope / Lifecycle), identify the bottleneck, and produce a prioritized improvement plan. Use when assessing if a project is ready to graduate to [LONG-RUN] status, when an agent keeps failing despite good models, or when adopting our stack on a new codebase. Do NOT use to design or build a new harness from scratch — this only scores an existing one; for greenfield harness/agent architecture use harness-design (or agent-harness-design).
os-release
发布 AI Team OS 新版本的完整清单——预检、版本七处锁步、中英双语 CHANGELOG、双份 dist 构建、私有术语扫描、commit/tag、双仓推送、建 GitHub Release 条目并核对 latest 徽章、事后核对。当准备发版、补建漏掉的 Release 条目、或核对已发版本的线上状态时使用。
finishing-a-development-branch
Presents options for merge, PR, or cleanup. Use when work is complete, tests pass, and you must decide how to integrate.
test-first-bugs
Enforces a test-driven bug-fixing workflow. Use when a user reports a bug, failing code, an error, or asks to fix something.
cross-review
Verify an implementer's diff with an INDEPENDENT, different-vendor sub-agent (diff plus contract only); turn blocking issues into fix-tasks and loop until clean.
debug
Investigation-first debugging — gather evidence, form confirmed root-cause hypothesis, hand off to fix mode with diagnosis file. TRIGGER when: user reports a symptom or failing test with Python traceback, or asks to investigate a runtime/CI failure with reproducible evidence; phrases: "debug this failure", "why is X broken", "find the root cause of <error>", "investigate this CI failure". SKIP when: pure config quality issues (use `/foundry:audit`); broad system-wide diagnosis without traceback (use `/foundry:investigate`); user already knows the fix (use `/develop:fix`); non-Python project.
feature
TDD-first feature development — crystallise API as a demo test, drive implementation to pass it, run quality stack and progressive review loop. TRIGGER when: user asks to build new functionality, add a capability, or implement a feature in a Python project; phrases: "add X", "implement Y", "build Z feature", "create a new module for". SKIP when: bug fixes (use `/develop:fix`); refactoring without new behaviour (use `/develop:refactor`); non-Python projects; `.claude/` config changes (use `/foundry:manage`).
fix
Reproduce-first bug resolution — capture bug in failing regression test, apply minimal fix, run quality stack and review loop. TRIGGER when: user reports a bug, regression, or unexpected behaviour in Python code with a traceback, failing test, or issue number; phrases: "fix this bug", "repair X", "broken since Y", "test failing". SKIP when: CI-only failures without local traceback (use `/develop:debug` first); new features (use `/develop:feature`); `.claude/` config issues (use `/foundry:audit`); non-Python projects.
refactor
Test-first refactoring — audit coverage, add characterization tests, apply changes with safety net, run quality stack and review loop. TRIGGER when: user wants to restructure existing Python code without changing behaviour; phrases: "refactor X", "clean up Y", "extract Z", "restructure this module", "improve code quality". SKIP when: bug fixes (use `/develop:fix`); new features (use `/develop:feature`); mixed refactor+feature — run `/develop:refactor` first, then `/develop:feature`; non-Python projects.
night-market-operations
Run and ship this repo: make targets, artifacts, release runbook. Use when testing, linting, or releasing. Do not use for setup; use night-market-build-and-env.
tokf-run
Compress verbose CLI output with tokf before returning results. Activates for git, cargo, npm, docker, go, gradle, kubectl, and other supported commands.
ci-fixer
CI failures - read error, minimal fix, verify.
assertion-synthesizer
Generate test assertions from existing code implementation. Use when the user has implementation code without tests or incomplete test coverage, and needs assertions synthesized by analyzing the code's behavior, inputs, outputs, and state changes. Supports Python (pytest/unittest), Java (JUnit/AssertJ), and JavaScript/TypeScript (Jest/Chai). Handles equality checks, collections, exceptions, and state verification.
behavior-preservation-checker
Compare runtime behavior between original and migrated repositories to detect behavioral differences, regressions, and semantic changes. Use when validating code migrations, refactorings, language ports, framework upgrades, or any transformation that should preserve behavior. Automatically compares test results, execution traces, API responses, and observable outputs between two repository versions. Provides actionable guidance for fixing deviations and ensuring behavioral equivalence.
bug-reproduction-test-generator
Automatically generates executable tests that reproduce reported bugs from issue reports and code repositories. Use when users need to: (1) Create a test that reproduces a bug described in an issue report, (2) Generate failing tests from bug descriptions, stack traces, or error messages, (3) Validate bug reports by creating reproducible test cases, (4) Convert issue reports into executable regression tests. Takes a repository and issue report as input and produces test code that reliably triggers the reported bug.
ci-pipeline-synthesizer
Generate GitHub Actions CI/CD pipeline configurations for automated building and testing of library and package projects. Use when creating or updating CI workflows for npm packages, Python packages, Go modules, Rust crates, or other library projects that need automated build and test pipelines. Includes templates for common package ecosystems with best practices for dependency caching, matrix testing, and artifact publishing.
configuration-generator
Generate configuration files for applications, services, and infrastructure. Use when: (1) Setting up new projects (package.json, requirements.txt, tsconfig.json), (2) Creating Docker or Kubernetes configurations, (3) Configuring CI/CD pipelines (GitHub Actions, GitLab CI, CircleCI), (4) Setting up web servers (Nginx, Apache), (5) Defining infrastructure as code (Terraform, CloudFormation), (6) Generating linter/formatter configs (ESLint, Prettier, Black). Provides templates and custom-generated configs for diverse tech stacks.
counterexample-explainer
Explain why counterexamples violate specifications by analyzing formal specifications (temporal logic, invariants, pre/postconditions, code contracts), informal requirements (user stories, acceptance criteria), test specifications (assertions, property-based tests), and providing step-by-step traces showing state changes, comparing expected vs actual behavior, identifying root causes, and assessing violation impact. Use when debugging test failures, understanding model checker output, explaining runtime assertion violations, analyzing static analysis warnings, or teaching specification concepts. Produces structured markdown explanations with traces, comparisons, state diagrams, and cause chains. Triggers when users ask why something failed, explain a violation, understand a counterexample, debug a specification, or analyze why a test fails.
coverage-enhancer
Analyze existing test suites and source code to suggest additional unit tests that improve test coverage. Use this skill when working with test files and source code to identify untested code paths, missing edge cases, uncovered branches, untested error conditions, and gaps in test coverage. Supports major testing frameworks (pytest, Jest, JUnit, Go testing, etc.) and generates targeted test suggestions based on coverage analysis.
cao-agent-routing
Find and select the best installed CAO agent profile for a task before delegating with assign or handoff. Use when a supervisor needs to route coding, documentation, infrastructure, review, research, or other specialist work and the user has not already chosen an agent profile.
loom-python
Python language expertise for idiomatic, production-quality code.
api-testing
API testing from OpenAPI/Swagger or case schemas: parameters, boundaries, auth, idempotency, concurrency, error responses, data consistency; runnable scripts; k6 handoff. Not for: Web UI flows, manual case writing. 接口级测试：参数/边界/鉴权/幂等/并发/错误响应/数据一致性，产出脚本与结果；含 k6 压测。不用于：Web UI、手动用例。
automated-e2e-testing
Turn manual cases into Playwright E2E automation run in a browser: page objects, helpers, bug evidence, reports. Not for: API tests, exploratory sessions, bug root-cause. 将手动用例转为 Playwright E2E 自动化并真实执行；含写自动化前的业务熟悉踩点、Page Object/Helper、Bug 证据与报告条目。不用于：API 接口测试、独立探索会话（exploratory-testing）、Bug 根因。
bug-analysis
对已确认的 Bug 做根因定位、影响分析、回归建议时使用——复现 → 读代码定位根因 → 影响五面分析 → 回归建议，条目（根因/影响/Severity 依据/修复建议/回归建议五个扩展字段）落盘为 Bug 条目。不用于：仅收集 Bug 证据（automated-e2e-testing / api-testing）、疑似未定性缺陷（test-case-writing 的 Cx 记录）。
exploratory-testing
Exploratory testing sessions when requirements are vague or docs are missing — charter-driven; outputs system understanding, risks, test ideas. Not for: automation prep, executing existing cases. 需求不完整、文档不足或系统陌生时发起独立探索式测试会话——charter 驱动，产出系统理解/风险清单/测试想法。不用于：为写自动化踩点（automated-e2e-testing 前置）、按既有用例执行。
qa
End-to-end QA entry: "test this feature fully" orchestrates requirements, strategy, cases, review, execution, bugs, regression, report; resumable. Single-stage tasks use their stage skill. 端到端测试唯一入口：“帮我测试这个需求/功能”时编排需求→策略→用例→审查→执行→Bug 分析→回归→报告，落盘可续跑；单阶段诉求直接用对应阶段 skill。
qa-memory
Maintain the .qa/ knowledge base of cross-session QA knowledge (quirks, flaky verdicts, defect patterns, contract changes); read before test tasks. Not for: pipeline state, case files (test-case-writing). 维护被测项目 .qa/ 跨会话知识库（环境怪癖、flaky、缺陷模式、契约变更）读写治理；任务前先读取。不用于：流水线状态、用例文件读写（test-case-writing）。
regression-testing
After a code change (diff/fix/requirement change), decide what to regression-test: changed files → functions → features → cases traceability; outputs a ranked list. Not for: editing case files (test-case-writing), long-term strategy (test-strategy). 代码变更后判断回归哪些测试：沿改动分析链产出分级回归清单。不用于：用例增量修改、长期策略。
requirement-analysis
Model a requirement/system: extract goals, scope, roles, rules, exceptions, dependencies from PRD, docs, bugs, code; outputs a structured model with clarifications. Not for: writing cases, strategy decisions, the pipeline. 建模需求/系统：从 PRD、文档、Bug、代码提炼目标/范围/角色/规则/异常/依赖。不用于：直接写用例、策略、流水线。
test-case-review
Review existing test cases (legacy, others', AI) for coverage and executability: build a testable-points baseline, assess independently, revise in place with records. Not for: writing cases from scratch (test-case-writing), pipeline. 审查已有用例（存量/他人/AI 产出）的覆盖与可执行性：先建基准再独立评估，修订留审查记录。不用于：从零写用例、写时自审、流水线。
test-case-writing
Write manual test cases (markmap) from docs, bugs or code — code-first: review code for bugs first; extracts machine-readable schema. Not for: requirement-analysis / test-strategy / test-case-review / automation. 从 PRD/API 文档、Bug 或代码写手动用例（markmap）——代码优先：先查代码找 bug 再写，抽 Schema。不用于：需求建模、策略、评审、自动化。
test-reliability
Govern flaky tests and suite reliability: rerun-pass verdicts, root-cause classes, quarantine, retry semantics, health metrics. Not for: in-run failures (e2e/api), triage, confirmed bugs. 治理 flaky 测试与套件可靠性：时好时坏/重跑变绿判定、根因四分类、隔离门禁、重试诚实语义、健康度。不用于：执行中单条失败（e2e/api）、批量分流（triage）、已确认 Bug（bug-analysis）。
test-strategy
"How should this be tested?" Evidence-backed risk map → scope and depth across functional domains and 10 testing-type axes; includes carry signals, excludes reasons. Not for: writing cases, requirement-analysis, pipeline (qa). 回答“这个功能应该怎么测”：风险挂证据（Risk Map），译为功能域+类型域十轴的范围与深度。不用于：写用例、需求建模、流水线。
test-fixing
Run tests and systematically fix all failing tests using smart error grouping. Use when user asks to fix failing tests, mentions test failures, runs test suite and failures occur, or requests to make tests pass.
autonomous-tdd-debugger
Empowers the agent to autonomously run tests, read terminal stack traces, and self-heal code until tests pass. Transforms the agent from a passive coder to an active CI pipeline debugger.
python-env
Fast Python environment management with uv (10-100x faster than pip). Triggers on: uv, venv, pip, pyproject, python environment, install package, dependencies.
python-pytest-patterns
pytest testing patterns for Python. Triggers on: pytest, fixture, mark, parametrize, mock, conftest, test coverage, unit test, integration test, pytest.raises.
python-services
Python patterns for CLI tools, async concurrency, and backend services. Use when working with Python code, building CLI apps, FastAPI services, async with asyncio, background jobs, or configuring uv, ruff, ty, pytest, or pyproject.toml.
writing-tests
Generic test writing discipline: test quality, real assertions, anti-patterns, and rationalization resistance. Use when writing tests, adding test coverage, or fixing failing tests for any language or framework. Complements language-specific skills.
tdd-workflow
Test-driven development enforcement with RED-GREEN-IMPROVE cycle
verification-loop
Pre-commit verification with lint, type-check, tests, and security scan
pyo3-bindings
PyO3 conventions for exposing a Rust core to Python: pyclass/pymethods, PyErr/PyResult error mapping, GIL release, properties, maturin builds, and pytest. Load when generating or reviewing PyO3 Python bindings for a Rust library.
python-conventions
Python code conventions covering type hints, Ruff formatting/linting, mypy/pyright, pytest, async I/O, uv packaging, and dependency security scanning. Load when writing or reviewing Python code.
robotics-testing
Testing strategies, patterns, and tools for robotics software. Use this skill when writing unit tests, integration tests, simulation tests, or hardware-in-the-loop tests for robot systems. Trigger whenever the user mentions testing ROS nodes, pytest with ROS, launch_testing, simulation testing, CI/CD for robotics, test fixtures for sensors, mock hardware, deterministic replay, regression testing for robot behaviors, or validating perception/planning/control pipelines. Also covers property-based testing for kinematics, fuzz testing for message handlers, and golden-file testing for trajectories.
environment-setup
Analyzes the project repository and guides the user through full local development environment setup — runtime tools, services, configuration, test toolchain, and verification. Use when running /sddp-devsetup.
core
qa-skills shared knowledge base — dependency, NOT triggerable: executability standards, evidence grading, risk model, type matrix, templates, scripts. Never invoke standalone; always install with the skills, or references break. 共享知识库（依赖单元，非触发 skill）：承载全系列引用的方法/模板/脚本。任何测试任务不要独立触发；装其他 skill 必须连装。
tdd
Test-driven development — write a failing test that names the behavior, watch it fail, implement the minimum to make it pass, then refactor with tests green. Works for new features, bug fixes, and behavior changes. Use when the user says "tdd", "test-first", "write tests first", or wants a change built test-first.
ia-python-services
Python patterns for CLI tools, async concurrency, and backend services. Use when working with Python code, building CLI apps, FastAPI services, async with asyncio, background jobs, or configuring uv, ruff, ty, pytest, or pyproject.toml.
readme-generator
Generate or refactor project README.md files using repository evidence. Use when the user asks to create/rewrite/standardize README, improve documentation structure, or produce maintainable README templates for different project types (service/library/CLI/monorepo).
agf-running-sit-tests
Use when an execution-layer dev (frontend-dev / backend-dev / ai-agent-dev / ml-engineer / miniapp-dev) has finished feature code + Unit tests and is about to enter code-review. Provides the SIT scope, environment, AC-driven integration walk, and evidence sink (progress/<role>.md). SIT is now a dev-owned step, not a separate QA stage.
testing
Generate, execute, and analyze tests for codebases, covering unit, integration, and end-to-end testing with coverage reporting. Use when the user requests testing or provides relevant inputs for this workflow.
pair-programming
AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score verification.
python-dev
Opinionated Python development setup with uv, ty, ruff, pytest, lefthook, and just. Use when creating a new Python project, writing or fixing pyproject.toml, or configuring linting, formatting, type checking, testing, git hooks, or CI.
sandbox
Execute commands in isolated sandboxes for security. Use when running untrusted code, system commands, or operations that could affect the host system. Automatically detects the right runtime (Python, Node, Rust, Go, Ruby, etc.) from the command.
integration
Run integration and e2e tests after unit tests pass. Use after /supergraph:fix when unit tests are green.
scan
Scan project once per session. Run first — all other skills depend on this.
telemetry
Unified pipeline telemetry — collects per-stage performance metrics (CPU, memory, I/O) and diagnostic events into structured reports (JSON, text).
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