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

Assessment: Ready for execution

Strengths:

• [Key strength 1]
• [Key strength 2]

Recommendations (optional):

• [Minor improvement 1]

Low Confidence (<7)

Confidence Score: 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

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

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