This skill teaches agents how to assess task complexity, enforce quality gates, and prevent wasted work on incomplete or poorly-defined tasks.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionquality-gatesExecute the skills CLI command in your project's root directory to begin installation:
Fetches quality-gates from yonatangross/orchestkit and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate quality-gates. Access via /quality-gates in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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This skill teaches agents how to assess task complexity, enforce quality gates, and prevent wasted work on incomplete or poorly-defined tasks.
Key Principle: Stop and clarify before proceeding with incomplete information. Better to ask questions than to waste cycles on the wrong solution.
| Level | Files | Lines | Time | Characteristics |
|---|---|---|---|---|
| 1 - Trivial | 1 | < 50 | < 30 min | No deps, no unknowns |
| 2 - Simple | 1-3 | 50-200 | 30 min - 2 hr | 0-1 deps, minimal unknowns |
| 3 - Moderate | 3-10 | 200-500 | 2-8 hr | 2-3 deps, some unknowns |
| 4 - Complex | 10-25 | 500-1500 | 8-24 hr | 4-6 deps, significant unknowns |
| 5 - Very Complex | 25+ | 1500+ | 24+ hr | 7+ deps, many unknowns |
Load: Read("${CLAUDE_SKILL_DIR}/references/complexity-scoring.md") for detailed examples and assessment formulas.
| Condition | Threshold | Action |
|---|---|---|
| YAGNI Gate | Justified ratio > 2.0 | BLOCK with simpler alternatives |
| YAGNI Warning | Justified ratio 1.5-2.0 | WARN with simpler alternatives |
| Critical Questions | > 3 unanswered | BLOCK |
| Missing Dependencies | Any blocking | BLOCK |
| Failed Attempts | >= 3 | BLOCK & ESCALATE |
| Evidence Failure | 2 fix attempts | BLOCK |
| Complexity Overflow | Level 4-5 no plan | BLOCK |
WARNING Conditions (proceed with caution):
Load: Read("${CLAUDE_SKILL_DIR}/references/blocking-thresholds.md") for escalation protocols and decision logic.
Load on demand with Read("${CLAUDE_SKILL_DIR}/references/<file>"):
| File | Content |
|---|---|
complexity-scoring.md |
Detailed Level 1-5 characteristics, quick assessment formula, checklist |
blocking-thresholds.md |
BLOCKING vs WARNING conditions, escalation protocol, gate decision logic, attempt tracking |
workflows.md |
Pre-task gate validation, stuck detection, complexity breakdown (Level 4-5), requirements completeness |
gate-patterns.md |
Gate validation process templates, context system integration, common pitfalls |
llm-quality-validation.md |
LLM-as-judge patterns, quality aspects, fail-open/closed strategies, graceful degradation, triple-consumer artifacts |
0. YAGNI check (runs FIRST — before any implementation planning)
→ Read project tier from scope-appropriate-architecture
→ Calculate justified_complexity = planned_LOC / tier_appropriate_LOC
→ If ratio > 2.0: BLOCK (must simplify)
→ If ratio 1.5-2.0: WARN (present simpler alternative)
→ Security patterns exempt from YAGNI gate
1. Assess complexity (1-5)
2. Count critical questions unanswered
3. Check dependencies blocked
4. Check attempt count
if (yagni_ratio > 2.0) -> BLOCK with simpler alternatives
else if (questions > 3 || deps blocked || attempts >= 3) -> BLOCK
else if (complexity >= 4 && no plan) -> BLOCK
else if (yagni_ratio > 1.5 || complexity == 3 || questions 1-2) -> WARNING
else -> PASS
## Quality Gate: [Task Name]
**Complexity:** Level [1-5]
**Unanswered Critical Questions:** [Count]
**Blocked Dependencies:** [List or None]
**Failed Attempts:** [Count]
**Status:** PASS / WARNING / BLOCKED
**Can Proceed:** Yes / No
## Escalation: Task Blocked
**Task:** [Description]
**Block Type:** [Critical Questions / Dependencies / Stuck / Evidence]
**Attempts:** [Count]
### What Was Tried
1. [Approach 1] - Failed: [Reason]
2. [Approach 2] - Failed: [Reason]
### Need Guidance On
- [Specific question]
**Recommendation:** [Suggested action]
// Add gate check to context
context.quality_gates = context.quality_gates || [];
context.quality_gates.push({
task_id: taskId,
timestamp: new Date().toISOString(),
complexity_score: 3,
gate_status: 'pass', // pass, warning, blocked
critical_questions_count: 1,
unanswered_questions: 1,
dependencies_blocked: 0,
attempt_count: 0,
can_proceed: true
});
// Before marking task complete
const evidence = context.quality_evidence;
const hasPassingEvidence = (
evidence?.tests?.exit_code === 0 ||
evidence?.build?.exit_code === 0
);
if (!hasPassingEvidence) {
return { gate_status: 'blocked', reason: 'no_passing_evidence' };
}
Track success/failure patterns across projects to prevent repeating mistakes and proactively warn during code reviews.
| Rule | File | Key Pattern |
|---|---|---|
| YAGNI Gate | rules/yagni-gate.md |
Pre-implementation scope check, justified complexity ratio, simpler alternatives |
| Pattern Library | rules/practices-code-standards.md |
Success/failure tracking, confidence scoring, memory integration |
| Review Checklist | rules/practices-review-checklist.md |
Category-based review, proactive anti-pattern detection |
| Level | Meaning | Action |
|---|---|---|
| Strong success | 3+ projects, 100% success | Always recommend |
| Mixed results | Both successes and failures | Context-dependent |
| Strong anti-pattern | 3+ projects, all failed | Block with explanation |
| Pitfall | Problem | Solution |
|---|---|---|
| Skip gates for "simple" tasks | Get stuck later | Always run gate check |
| Ignore WARNING status | Undocumented assumptions cause issues | Document every assumption |
| Not tracking attempts | Waste cycles on same approach | Track every attempt, escalate at 3 |
| Proceed when BLOCKED | Build wrong solution | NEVER bypass BLOCKED gates |
ork:scope-appropriate-architecture - Project tier detection that feeds YAGNI gateork:architecture-patterns - Enforce testing standards as part of quality gatesllm-evaluation - LLM-as-judge patterns for quality validationork:golden-dataset - Validate datasets meet quality thresholds| Decision | Choice | Rationale |
|---|---|---|
| Complexity Scale | 1-5 levels | Granular enough for estimation, simple enough for quick assessment |
| Block Threshold | 3 critical questions | Prevents proceeding with too many unknowns |
| Escalation Trigger | 3 failed attempts | Balances persistence with avoiding wasted cycles |
| Level 4-5 Requirement | Plan required | Complex tasks need upfront decomposition |
Keywords: complexity, score, difficulty, estimate, sizing, 1-5 scale Solves: How complex is this task? Score task complexity on 1-5 scale, assess implementation difficulty
Keywords: blocking, threshold, gate, stop, escalate, cannot proceed Solves: When should I block progress? >3 critical questions = BLOCK, Missing dependencies = BLOCK
Keywords: critical questions, unanswered, unknowns, clarify Solves: What are critical questions? Count unanswered, block if >3
Keywords: stuck, failed attempts, retry, 3 attempts, escalate Solves: How do I detect when stuck? After 3 failed attempts, escalate
Keywords: validate, gate check, pass, fail, gate status Solves: How do I validate quality gates? Run pre-task gate validation
Keywords: pre-task, before starting, can proceed Solves: How do I check gates before starting? Assess complexity, identify blockers
Keywords: breakdown, decompose, subtasks, split task Solves: How do I break down complex tasks? Split Level 4-5 into Level 1-3 subtasks
Keywords: requirements, incomplete, acceptance criteria Solves: Are requirements complete enough? Check functional/technical requirements
Keywords: escalate, ask user, need help, human guidance Solves: When and how to escalate? Escalate after 3 failed attempts
Keywords: llm as judge, g-eval, aspect scoring, quality validation Solves: How do I use LLM-as-judge? Evaluate relevance, depth, coherence with thresholds
Keywords: yagni, over-engineering, justified complexity, scope check, too complex, simplify Solves: Is this complexity justified? Calculate justified_complexity ratio against project tier, BLOCK if > 2.0, surface simpler alternatives
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
quality-gates is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in quality-gates — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Keeps context tight: quality-gates is the kind of skill you can hand to a new teammate without a long onboarding doc.
Solid pick for teams standardizing on skills: quality-gates is focused, and the summary matches what you get after install.
quality-gates reduced setup friction for our internal harness; good balance of opinion and flexibility.
quality-gates has been reliable in day-to-day use. Documentation quality is above average for community skills.
Registry listing for quality-gates matched our evaluation — installs cleanly and behaves as described in the markdown.
quality-gates fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
I recommend quality-gates for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added quality-gates from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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