Verification loop for Django projects: migrations, linting, tests with coverage, security scans, and deployment readiness checks before release or PR.
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Verification loop for Django projects: migrations, linting, tests with coverage, security scans, and deployment readiness checks before release or PR.
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[AUTO-INVOKE] MUST be invoked BEFORE deploying contracts or writing deployment scripts (*.s.sol). Covers pre-flight checks, forge script commands, post-deployment validation, and verification. Trigger: any task involving forge script, contract deployment, or block explorer verification.
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根据 MAS + verification_plan + RTL 接口描述生成 SystemVerilog UVM 或 cocotb 测试平台与 test cases 清单。触发场景:(1) bba-guru-verification 在 plan 完成后;(2) 补充 corner case TB;(3) 显式 /bb-generate-tb。
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Independent LLM judge evaluates task completion separately from the executing agent, catching false success claims by reviewing task goal, actions taken, final state, and evidence. Produces PASS/FAIL with confidence score and reasoning.
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Verify that task outputs actually achieve stated goals through 4 progressive levels of verification
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Apply software pipelining (double-buffering) to a tiled GPU kernel to overlap global memory loads with Tensor Core computation. Covers prologue/loop/epilogue restructuring, LDG-register vs cp.async (LDGSTS) variant selection based on compute/load ratio, shared memory budget verification against architecture-specific occupancy cliffs, and SASS-level verification of load/compute overlap.
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Thoroughness and diligence in execution — systematic checking, completeness verification, follow-through on commitments, and the discipline of finishing well. Maps the personality trait of conscientiousness to AI task execution: not cutting corners, verifying results, and ensuring that what was promised is what was delivered. Use before marking a task as complete, when a response feels "good enough" but deserves better, after a complex multi-step operation where steps may have drifted, or when self-monitoring detects a pattern of cutting corners or rushing.
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Use when effectful, security-sensitive code needs refinement-typed, SMT-backed verification in F*, in the HACL* or Project Everest style.
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Write well-structured Verification Guards. Use when: (1) Creating a new guard, (2) Editing guard check commands or patterns, (3) User mentions guard, verification, or check
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Verify NowStack Mobile iOS/Expo changes in the Apple Simulator with `xcrun simctl`. Covers single or parallel Metro/device flows, deep-link navigation, preview routes, and OTP sign-in. Use for `ns ios verification`, "test on simulator", or changed `mobile-app/**`; never use computer-use.
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Use this skill when writing Phase 1b verification architecture documents. Provides purity boundary mapping, proof obligation design, and tier assignment guidance.
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设计 Loop 的 Goal 和 Verification 环节: 将模糊目标转化为可验证的停止条件。 当用户发现 loop 产出质量不稳定、循环无法停止、或"不知道什么时候算做完"时使用。 不适用于: 目标已经非常清晰可量的任务、或非循环场景。 关键 trigger: "loop 停不下来"、"产出质量不稳定"、"怎么定义完成"、"goal 怎么写"。
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Comprehensive fix verification methodology to ensure bugs are truly fixed. Use after implementing any bug fix to verify it works and hasn't caused regressions. Keywords: verify, confirm, test, validate, check, ensure, regression, fixed
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Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always
日本語の概要は準備中です。原文の説明を表示しています。
Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always
日本語の概要は準備中です。原文の説明を表示しています。
Run an explicit end-to-end goal loop with frozen Scope/criteria, worker delegation, external verification, evaluator review, and bounded retries. Use when the user asks for 'goal-loop', 'ゴールまで回す', '必ずやり遂げる', 'loop until done', 'until it actually works', or an orchestrator + evaluator loop. Do not use for ordinary planning, casual advice, reviews, or small single-file fixes.
Build and validate Azure infrastructure in a lab or sandbox using Azure CLI and official Microsoft docs. Use when creating verification environments, provisioning hub-and-spoke VNets, VPN Gateway or ExpressRoute-adjacent validation labs, checking subscription/tenant access, debugging Azure deployment constraints, comparing before/after route behavior, or cleaning up lab resources. Triggers on 'Azure 検証', '検証環境', 'PoC', 'sandbox', 'lab', 'Azure CLI で構築', 'VPN Gateway', 'VNet peering', 'BGP', 'route validation', 'summarizedGatewayPrefixes', 'デプロイして検証', 'インフラ検証'.
Implement a single Flutter task following this repository's Riverpod, Freezed, AutoRoute, DTO/entity, codegen, and verification conventions. Reads the task definition, PRD, and tech spec, then executes the implementation. When invoked standalone, verifies the change; when invoked by implement-tasks-sequence, writes code only and leaves verification to start-job/build-verify. Use when the user says "implement task X", "work on task X", or wants to execute a specific task from the task list.
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Build/test/lint verification pass for this Flutter app — runs codegen, analyze, test, then iOS + Android native builds in parallel, then `dart format`. Does NOT commit anything; leaves the working tree dirty so the user can review and commit on demand. Used at the end of the prd → techspec → tasks → implement-tasks-sequence flow before `pr-review`, and can also be invoked manually when the user says "verify build", "run full verification", or "check everything".
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5-level verification pyramid: static→unit→Playwright E2E (homepage-first, 6bp)→AI visual→post-deploy. 8-check quality gate. Multi-agent testing (functional/security/a11y/performance). Playwright v1.56+ AI agents (Planner/Generator/Healer, v1.63 current). WCAG 2.2 AA via axe-core v4.13. Percy+Chromatic visual regression. ADA Title II 2027/2028 deadlines.
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Phase 2B of the Gaia evidence verification pipeline. Verifies benchmark-result rows and benchmark-source candidates against registry/benchmark-sources.json before adversarial audit, link validation, catalog promotion, or ingestion. Use when running /ev-pipeline, checking benchmark-result evidence, reviewing benchmark-source candidates, or preparing benchmark rows for /gaia-ingest-batch.
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Orchestrate a whole-registry sweep of Gaia — fan out 13 parallel audit agents across every skill, run adversarial verification, surface Semantic Fusion candidates, propose new generic skill references, and synthesize a publish-ready HTML report under docs/meta/reports/. Use this skill for broad, systemic analysis across many skills at once: "run a meta sweep", "sweep the meta", "full meta audit", "audit the whole registry against META.md", "widespread nomenclature issues", "find all skills missing a GitHub link", "produce a meta report", "check for evidence type mismatches across the registry", "find skills that document a third-party tool with no attribution", or explicitly types /gaia-meta-sweep. This is the registry-wide macro companion to /gaia-meta-audit (a prioritized queue, single-pass) and /gaia-audit (fixes one skill). Use it when you need the full surface — 13 audit dimensions, adversarial verification, fusion proposals, and a durable findings artifact — not just a queue.
日本語の概要は準備中です。原文の説明を表示しています。
Phase 1 of the Gaia evidence verification pipeline. Use this skill whenever you need to gather, consolidate, or refresh raw evidence for named skills in the registry. Trigger phrases: "collect evidence", "populate the data lake", "gather sources", "run ev-collection", "Phase 1", "compile the evidence index", "refresh the unified lake", "aggregate skill evidence", "build the evidence database". Also invoke as the first step before running ev-star-verification, ev-adversarial-audit, or ev-link-validation — nothing downstream is meaningful without a fresh, compiled index. Covers GitHub repo links, stargazer signals, YouTube showcases, arXiv papers, peer reviews, benchmark results, blog/newsletter posts, and self-attestation artifacts.
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Use when a task needs the judgment of a biomedical/bioengineering engineer — running a design control phase (inputs, outputs, verification, validation) for a medical device, scoring a Design FMEA and deciding whether a failure mode needs mitigation, planning a human factors/usability validation study, building a design traceability matrix, or writing a design verification or risk-mitigation report. Distinct from a regulatory-affairs-specialist (owns the submission/clearance process, not the engineering itself) and from a clinical-data-manager/biostatistician (trial data and analysis, not device design).
日本語の概要は準備中です。原文の説明を表示しています。