Results for “quality-gates”

Coordinates five specialized coding agents (linter, perf, refactor, security, test) to enforce quality gates across the development lifecycle, from lint enforcement through performance profiling, refactoring, security auditing, and test coverage.

Defines quality standards and validation checklists for agent workflows, Python tools, and documentation, including automated checks and pre-commit gates.

CQO quality and operational governance lead. Owns gates, regression strategy, memory hygiene, port/service policy, and archive approval.

Runs and writes tests, verifies behavior, and orchestrates two-pass TDD across scoped modes, blocking on quality gates and never editing production code.

Audits code quality against a shared contract, producing structured findings and blocking pipeline phases on critical issues without modifying code.

Decide whether an article deserves publication through hard checks and skeptical comparison.

QA Testing

Run full quality gate suite before committing or creating a PR

Guardian of V.A.I.R.E. quality standards (Value/Agency/Identity/Resilience/Echo). Handles pre-release evaluation, scorecard assessment, and pass/fail determination. Use when UX quality gates are needed. Does not write code.

Implements features and writes code based on Plans.md tasks, with quality gates and routing to sub-skills for feature implementation and test writing.

Fact-forcing gate that blocks Edit/Write/Bash (including MultiEdit) and demands concrete investigation (importers, data schemas, user instruction) before allowing the action. Measurably improves output quality by +2.25 points vs ungated agents.

Blocks Edit/Write/Bash actions until the agent presents concrete facts about imports, data schemas, and the user's instruction, improving output quality.

Fact-forcing gate that blocks Edit/Write/Bash (including MultiEdit) and demands concrete investigation (importers, data schemas, user instruction) before allowing the action. Measurably improves output quality by +2.25 points vs ungated agents.

Gate de qualidade final do plugin civel. Aplica 4 validacoes (R1 fatos/competencia/foro, R2 fundamentacao legal vigente, R3 jurisprudencia real verificada, R4 forma/pedidos/tempestividade/valor da causa/gratuidade) antes de qualquer entrega. Use SEMPRE antes de entregar peca, recurso, manifestacao ou parecer; acionada pelo civel-master ao fechar qualquer ato. Tambem quando o operador disser revisao final, valida antes de entregar, /revisao-final.

Gatekeeping Git/PR by classifying change essence and recommending granularity, naming, and strategy. Use when PR preparation or commit strategy is needed.

Post-implementation quality gate that reviews changes, fixes small issues (scout rule), creates tasks for medium issues, and generates analysis for large issues.

Post-implementation quality gate that reviews changes, fixes small issues (scout rule), creates tasks for medium issues, and generates analysis for large issues.

AI QA and evaluation specialist for quality gates. Use when the user asks to talk to Moody, requests AI evaluation, or needs regression tests for AI systems.

Forces AI agents to investigate before editing or running destructive commands, improving code quality by requiring concrete facts like importers, data schemas, and user instructions.

Skill Tester

Fact-forcing gate that blocks Edit/Write/Bash (including MultiEdit) and demands concrete investigation (importers, data schemas, user instruction) before allowing the action. Measurably improves output quality by +2.25 points vs ungated agents.

Conducts multi-axis code review across correctness, readability, architecture, security, and performance before merging any change.

Skill Tester

Enforces running verification commands and confirming output before claiming work is complete, fixed, or passing, to prevent false success claims.

Guides the creation, editing, and verification of agent skills using a test-driven development approach, with structured documentation and quality gates.

Refactors production code with test coverage using a TDD workflow that applies approved refactorings one at a time, gates each on passing tests, and commits or reverts accordingly.

Creates a GitHub pull request with an auto-generated summary, running mandatory pre-commit and code-quality review gates, plus optional deep-review subagents, and posts findings into the PR body.

Screen US stocks for Stockbee-style selling-exhaustion hammer setups using prior momentum, pullback depth, undercut/reclaim, long lower-wick geometry, close-location, volume confirmation, quality/liquidity gates, and risk-distance scoring.

>- Skill Refiner, the eval-guided improvement loop for SKILL.md files. Runs the bootstrap, score, propose, apply, and status cycle as a thin wrapper over the published @intentsolutions/refiner CLI, proposing safe, minimal, bounded SKILL.md edits and accepting an edit only when a held-out eval score strictly improves with no regression on any other case. Ships a 3-layer cost-tiered hook architecture (sinker, line, hook) that gates skill quality at edit time, end of turn, and commit time. Use when improving an existing skill, refining a SKILL.md against measured behavior, bootstrapping an eval set for a skill, or gating skill edits before they ship. Trigger with "/j-rig", "refine this skill", "bootstrap an eval set", "propose a skill edit", "promote the candidate", or "skill refiner status".