How do I install the Testing Quality skill?

Run npx skillmds@latest add majiayu000/testing-quality in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Testing Quality safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Testing Quality?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Testing Quality free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Testing Quality?

majiayu000 (@majiayu000) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Testing Quality by majiayu000 — Agent Skill

Name: Testing Quality
Rating: 4.5 (4 reviews)
Author: majiayu000

File contents

STANDARD OPERATING PROCEDURE

Purpose

Provide a hub for research testing skills (code review, functionality audit, verification, style audit, theater detection).
Enforce constraint hygiene, quality gates, and explicit confidence ceilings on test results.
Maintain structure-first documentation for all sub-skills.

Trigger Conditions

Positive: any request to validate research code, results, or quality using the contained sub-skills.
Negative: non-research production testing (route to quality/operations categories).

Guardrails

Capture HARD / SOFT / INFERRED testing constraints (coverage targets, latency, risk tolerance, compliance).
Two-pass refinement: choose appropriate sub-skill(s) → validate findings with evidence and ceilings.
Route tasks to sub-skills: code-review-assistant, functionality-audit, verification-quality, style-audit, theater-detection.

Inputs

Artifact to test (code, models, data, results) and context.
Constraints and success criteria; environment details if applicable.

Workflow

Scope & Route: Record constraints and select relevant sub-skills; confirm INFERRED risks.
Plan Checks: Define coverage, tools, and expected outputs per sub-skill.
Execute Tests: Run selected skills, gather evidence, and log configurations.
Validate & Synthesize: Aggregate findings, mark severity, and apply confidence ceilings.
Deliver & Store: Provide consolidated report and next actions; update references/examples.

Validation & Quality Gates

Sub-skill selection justified and constraints mapped.
Evidence attached to findings; ceilings aligned to evidence type.
Recommendations include remediation steps and owners.

Response Template

**Scope & Constraints**
- HARD / SOFT / INFERRED.

**Selected Checks**
- Sub-skill → rationale.

**Findings**
- Issue → evidence → severity → confidence ceiling.

**Actions**
- Remediation + owner + due date.

Confidence: 0.81 (ceiling: inference 0.70) - based on executed checks and evidence.

Confidence: 0.81 (ceiling: inference 0.70) - reflects validated testing coverage and findings.

---name: testing-qualitydescription: Coordinate research-focused testing and quality validation with clear constraints, gates, and confidence ceilings.--- ## STANDARD OPERATING PROCEDURE ### Purpose - Provide a hub for research testing skills (code review, functionality audit, verification, style audit, theater detection). - Enforce constraint hygiene, quality gates, and explicit confidence ceilings on test results. - Maintain structure-first documentation for all sub-skills. ### Trigger Conditions - **Positive:** any request to validate research code, results, or quality using the contained sub-skills. - **Negative:** non-research production testing (route to quality/operations categories). ### Guardrails - Capture HARD / SOFT / INFERRED testing constraints (coverage targets, latency, risk tolerance, compliance). - Two-pass refinement: choose appropriate sub-skill(s) → validate findings with evidence and ceilings. - Route tasks to sub-skills: code-review-assistant, functionality-audit, verification-quality, style-audit, theater-detection. ### Inputs - Artifact to test (code, models, data, results) and context. - Constraints and success criteria; environment details if applicable. ### Workflow 1. **Scope & Route**: Record constraints and select relevant sub-skills; confirm INFERRED risks. 2. **Plan Checks**: Define coverage, tools, and expected outputs per sub-skill. 3. **Execute Tests**: Run selected skills, gather evidence, and log configurations. 4. **Validate & Synthesize**: Aggregate findings, mark severity, and apply confidence ceilings. 5. **Deliver & Store**: Provide consolidated report and next actions; update references/examples. ### Validation & Quality Gates - Sub-skill selection justified and constraints mapped. - Evidence attached to findings; ceilings aligned to evidence type. - Recommendations include remediation steps and owners. ### Response Template ``` **Scope & Constraints** - HARD / SOFT / INFERRED. **Selected Checks** - Sub-skill → rationale. **Findings** - Issue → evidence → severity → confidence ceiling. **Actions** - Remediation + owner + due date. Confidence: 0.81 (ceiling: inference 0.70) - based on executed checks and evidence. ``` Confidence: 0.81 (ceiling: inference 0.70) - reflects validated testing coverage and findings.

Frequently asked questions

Testing Quality