Agent-Skills.md

Agent Skills: Confidence Scoring for PRPs and Work-Orders

Assess quality of PRPs and work-orders using systematic confidence scoring. Use when evaluating readiness for execution or subagent delegation.

UncategorizedID: laurigates/claude-plugins/confidence-scoring

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laurigates/claude-plugins
laurigatesLicense: MIT
234

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blueprint-plugin/skills/confidence-scoring/SKILL.md

Skill Metadata

Name
confidence-scoring
Description
"Assess quality of PRPs and work-orders using systematic confidence scoring. Use when evaluating readiness for execution or subagent delegation."

Confidence Scoring for PRPs and Work-Orders

This skill provides systematic evaluation of PRPs (Product Requirement Prompts) and work-orders to determine their readiness for execution or delegation.

When to Use This Skill

Activate this skill when:

  • Creating a new PRP (/prp:create)
  • Generating a work-order (/blueprint:work-order)
  • Deciding whether to execute or refine a PRP
  • Evaluating whether a task is ready for subagent delegation
  • Reviewing PRPs/work-orders for quality

Scoring Dimensions

1. Context Completeness (1-10)

Evaluates whether all necessary context is explicitly provided.

| Score | Criteria | |-------|----------| | 10 | All file paths explicit with line numbers, all code snippets included, library versions specified, integration points documented | | 8-9 | Most context provided, minor gaps that can be inferred from codebase | | 6-7 | Key context present but some discovery required | | 4-5 | Significant context missing, will need exploration | | 1-3 | Minimal context, extensive discovery needed |

Checklist:

  • [ ] File paths are absolute or clearly relative to project root
  • [ ] Code snippets include actual line numbers (e.g., src/auth.py:45-60)
  • [ ] Library versions are specified
  • [ ] Integration points are documented
  • [ ] Patterns from codebase are shown with examples

2. Implementation Clarity (1-10)

Evaluates how clear the implementation approach is.

| Score | Criteria | |-------|----------| | 10 | Pseudocode covers all cases, step-by-step clear, edge cases addressed | | 8-9 | Main path clear, most edge cases covered | | 6-7 | Implementation approach clear, some details need discovery | | 4-5 | High-level only, significant ambiguity | | 1-3 | Vague requirements, unclear approach |

Checklist:

  • [ ] Task breakdown is explicit
  • [ ] Pseudocode is provided for complex logic
  • [ ] Implementation order is specified
  • [ ] Edge cases are identified
  • [ ] Error handling approach is documented

3. Gotchas Documented (1-10)

Evaluates whether known pitfalls are documented with mitigations.

| Score | Criteria | |-------|----------| | 10 | All known pitfalls documented, each has mitigation, library-specific issues covered | | 8-9 | Major gotchas covered, mitigations clear | | 6-7 | Some gotchas documented, may discover more | | 4-5 | Few gotchas mentioned, incomplete coverage | | 1-3 | No gotchas documented |

Checklist:

  • [ ] Library-specific gotchas documented
  • [ ] Version-specific behaviors noted
  • [ ] Common mistakes identified
  • [ ] Each gotcha has a mitigation
  • [ ] Race conditions/concurrency issues addressed

4. Validation Coverage (1-10)

Evaluates whether executable validation commands are provided.

| Score | Criteria | |-------|----------| | 10 | All quality gates have executable commands, expected outcomes specified | | 8-9 | Main validation commands present, most outcomes specified | | 6-7 | Some validation commands, gaps in coverage | | 4-5 | Minimal validation commands | | 1-3 | No executable validation |

Checklist:

  • [ ] Linting command provided and executable
  • [ ] Type checking command provided (if applicable)
  • [ ] Unit test command with specific test files
  • [ ] Integration test command (if applicable)
  • [ ] Coverage check command with threshold
  • [ ] Security scan command (if applicable)
  • [ ] All commands include expected outcomes

5. Test Coverage (1-10) - Work-Orders Only

Evaluates whether test cases are specified.

| Score | Criteria | |-------|----------| | 10 | All test cases specified with assertions, edge cases covered | | 8-9 | Main test cases specified, most assertions included | | 6-7 | Key test cases present, some gaps | | 4-5 | Few test cases, minimal detail | | 1-3 | No test cases specified |

Checklist:

  • [ ] Each test case has code template
  • [ ] Assertions are explicit
  • [ ] Happy path tested
  • [ ] Error cases tested
  • [ ] Edge cases tested

Calculating Overall Score

For PRPs

Overall = (Context + Implementation + Gotchas + Validation) / 4

For Work-Orders

Overall = (Context + Gotchas + TestCoverage + Validation) / 4

Score Thresholds

| Score | Readiness | Recommendation | |-------|-----------|----------------| | 9-10 | Excellent | Ready for autonomous subagent execution | | 7-8 | Good | Ready for execution with some discovery | | 5-6 | Fair | Needs refinement before execution | | 3-4 | Poor | Significant gaps, recommend research phase | | 1-2 | Inadequate | Restart with proper research |

Response Templates

High Confidence (7+)

## Confidence Score: X.X/10

| Dimension | Score | Notes |
|-----------|-------|-------|
| Context Completeness | X/10 | [specific observation] |
| Implementation Clarity | X/10 | [specific observation] |
| Gotchas Documented | X/10 | [specific observation] |
| Validation Coverage | X/10 | [specific observation] |
| **Overall** | **X.X/10** | |

**Assessment:** Ready for execution

**Strengths:**
- [Key strength 1]
- [Key strength 2]

**Recommendations (optional):**
- [Minor improvement 1]

Low Confidence (<7)

## Confidence Score: X.X/10

| Dimension | Score | Notes |
|-----------|-------|-------|
| Context Completeness | X/10 | [specific gap] |
| Implementation Clarity | X/10 | [specific gap] |
| Gotchas Documented | X/10 | [specific gap] |
| Validation Coverage | X/10 | [specific gap] |
| **Overall** | **X.X/10** | |

**Assessment:** Needs refinement before execution

**Gaps to Address:**
- [ ] [Gap 1 with suggested action]
- [ ] [Gap 2 with suggested action]
- [ ] [Gap 3 with suggested action]

**Next Steps:**
1. [Specific research action]
2. [Specific documentation action]
3. [Specific validation action]

Examples

Example 1: Well-Prepared PRP

## Confidence Score: 8.5/10

| Dimension | Score | Notes |
|-----------|-------|-------|
| Context Completeness | 9/10 | All files explicit, code snippets with line refs |
| Implementation Clarity | 8/10 | Pseudocode covers main path, one edge case unclear |
| Gotchas Documented | 8/10 | Redis connection pool, JWT format issues covered |
| Validation Coverage | 9/10 | All gates have commands, outcomes specified |
| **Overall** | **8.5/10** | |

**Assessment:** Ready for execution

**Strengths:**
- Comprehensive codebase intelligence with actual code snippets
- Validation gates are copy-pasteable
- Known library gotchas well-documented

**Recommendations:**
- Consider documenting concurrent token refresh edge case

Example 2: Needs Work

## Confidence Score: 5.0/10

| Dimension | Score | Notes |
|-----------|-------|-------|
| Context Completeness | 4/10 | File paths vague ("somewhere in auth/") |
| Implementation Clarity | 6/10 | High-level approach clear, no pseudocode |
| Gotchas Documented | 3/10 | No library-specific gotchas |
| Validation Coverage | 7/10 | Test command present, missing lint/type check |
| **Overall** | **5.0/10** | |

**Assessment:** Needs refinement before execution

**Gaps to Address:**
- [ ] Add explicit file paths (use `grep` to find them)
- [ ] Add pseudocode for token generation logic
- [ ] Research jsonwebtoken gotchas (check GitHub issues)
- [ ] Add linting and type checking commands

**Next Steps:**
1. Run `/prp:curate-docs jsonwebtoken` to create ai_docs entry
2. Use Explore agent to find exact file locations
3. Add validation gate commands from project's package.json

Integration with Blueprint Development

This skill is automatically applied when:

  • /prp:create generates a new PRP
  • /blueprint:work-order generates a work-order
  • Reviewing existing PRPs for execution readiness

The confidence score determines:

  • 9+: Proceed with subagent delegation
  • 7-8: Proceed with direct execution
  • < 7: Refine before execution

Tips for Improving Scores

Context Completeness

  • Use grep to find exact file locations
  • Include actual line numbers in code snippets
  • Reference ai_docs entries for library patterns

Implementation Clarity

  • Write pseudocode before describing approach
  • Enumerate edge cases explicitly
  • Define error handling strategy

Gotchas Documented

  • Search GitHub issues for library gotchas
  • Check Stack Overflow for common problems
  • Document team experience from past projects

Validation Coverage

  • Copy commands from project's config (package.json, pyproject.toml)
  • Include specific file paths in test commands
  • Specify expected outcomes for each gate