Results for “quality-check”

Content quality and E-E-A-T analysis with AI citation readiness assessment. Use when user says "content quality", "E-E-A-T", "content analysis", "readability check", "thin content", or "content audit".

Runs a structured self-review checklist before committing substantial code changes, covering edge cases, error paths, test coverage, documentation, and code quality.

Blocks Claude from finishing a session until deterministic quality checks pass: learning library freshness, disk space, and rationalization pattern detection.

Build evaluation frameworks for agent systems with deterministic checks, regression suites, multi-dimensional rubrics, quality gates, production monitoring, and outcome measurement.

Selects and curates still photos from ZIPs, folders, or event material, producing album and highlight selections with quality checks and delivery packages.

Reviews all pipeline artifacts from a virtual software team and produces quality, compliance, and sign-off reports with an advisory release verdict.

Language-specific best practices, code quality standards, and framework detection rules. Use when executing refactoring workflows, applying code quality rules, detecting frameworks, or checking language-specific patterns for TypeScript, Python, Go, Swift, or React.

Enforces a principal-engineer self-review checklist on every code block before output, covering correctness, performance, security, naming, and testability.

Use this skill for SEO checks in CI, metadata, canonicals, links, robots, sitemap, noindex regressions. Trigger when the task involves seo work related to SEO CI Quality Gate, implementation, audits, debugging, strategy, or validation.

Reduces AI API costs by 30-75% by classifying task complexity, checking prompt quality, and routing tasks to the most cost-efficient model tier before execution.

Audits Claude skills and commands for quality, offering Quick Scan for changed skills and Full Stocktake modes with sequential subagent batch evaluation.

Runs a structured quality control audit on codebases, covering tests, imports, static analysis, type checking, smoke tests, UI verification, file consistency, and documentation, producing a PASS/WARN/FAIL report.

Stages and commits changes with quality checks, status review, and a clear message, then shows recent history.

Provides code review best practices, checklists, and example feedback for quality, security, performance, and maintainability.

Use this agent when you need to run linting and code quality checks on Ruby and ERB files. Run before pushing to origin.

Prepare PRINCE2 Managing Product Delivery material: work package acceptance, team plans, checkpoint reports, quality evidence, delivery confirmation, and handback notes.

Enforce code quality with Ruff in a controlled, iterative workflow: run checks with optional scope and rule overrides, apply safe and unsafe autofixes, review diffs, and resolve remaining findings.

Runs and writes tests for a project, supporting unit, integration, and end-to-end scopes, plus two-pass TDD orchestration with quality-gate checks and regression sweeps.

Schema validation for notes. Checks against domain-specific templates. Validates required fields, enum values, description quality, and link health. Non-blocking — warns but doesn't prevent capture. Triggers on "/validate", "/validate [note]", "check schema", "validate note", "validate all".

Benchmark-relative quality gate. Scores the draft against the research dossier's beat spec (depth, consensus coverage, evidence) plus AI-tell and voice signals, runs an adversarial read armed with the SERP benchmark, and emits the verdict that gates the pipeline.

Runs a multi-phase verification pipeline including build, type-check, lint, tests, security scan, and diff review to ensure code quality before creating a PR.

Audit a proposed assessment for construct validity, reliability, and alignment to learning objectives. Use when reviewing or quality-assuring assessments before deployment.

Performs a comprehensive cross-artifact QA/QC review of a virtual team pipeline, checking completeness, consistency, security, and compliance, then issues an advisory verdict with quality, compliance, and sign-off reports.

Run a fast, read-only health check across all skills in the library and produce a structured quality report — without modifying anything. Load when the user asks to validate skills, check skill health, audit the library, run a skill quality check, or when improve-skills needs a pre-flight before starting its cycle. Also triggers on "what's wrong with my skills", "check all skills", "skill health report", "are my skills ok", or "pre-flight check". Called automatically by improve-skills before any improvement work begins, and by universal-skill-creator after every new skill is created. Never modifies any file — only reads and reports.

You are an expert in Soda, the data quality platform for testing, monitoring, and profiling data. You help developers write data quality checks in YAML that validate freshness, completeness, uniqueness, validity, and business rules — catching data issues before they reach dashboards and ML models.

This skill should be used when the user asks to "validate a plugin", "optimize plugin", "check plugin quality", "review plugin structure", or "run plugin optimizer".

Use when the user asks to review pull requests, analyze code changes, check for security issues in PRs, or assess code quality of diffs.

Pre-send email quality review and scoring across 5 dimensions (subject line, copy quality, technical/HTML, deliverability, compliance). Analyzes subject lines, body copy, HTML structure, spam triggers, and CAN-SPAM compliance. Scores 0-100 with detailed recommendations for improvement. Use when user wants to review an email before sending, check email quality, or validate marketing email best practices.

Performs a meticulous final pass on frontend work, checking visual alignment, typography, color contrast, interaction states, micro-interactions, content, icons, forms, edge cases, responsiveness, performance, and code quality to elevate work from shipped to polished.

Builds, edits, and analyzes workflows and skills. Use when the user requests to "build a workflow", "modify a workflow", "quality check workflow", or "analyze skill".

Python code-quality anti-patterns and review checks: exception-hierarchy correctness, singleton identity comparison, narrow exception handling, wildcard-import avoidance, magic-number naming, and dead-local removal. Use when reviewing or self-reviewing Python code for correctness and readability defects that linters and reviewers should catch.

Creates executable Polars dataframe contracts using Pandera's Polars backend for runtime validation of schemas, columns, and checks.

Apply-now consolidation of accreted CI gates, ratchets, and hooks into one aggregator required check. Use after audit-gate-logic, or when "clean up our CI checks", "we have three lint jobs", "make one quality gate". Audit-only → audit-gate-logic. Pipeline cost → audit-cicd.

Review local branch changes for bugs, security vulnerabilities, and code quality issues using a structured checklist-driven process.

Reviews local branch changes for bugs, security vulnerabilities, and code quality issues using a structured checklist and attack surface mapping.

Guides contributors through creating pull requests that add or fix skills, with a checklist covering metadata validation, risk labeling, and security disclaimers.