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MicrosoftKnown publishermicrosoft/haste/.github/skills/validation-diagnostics/SKILL.md

validation-diagnostics

Skill110 starsChanged 3 months agoMITView on GitHub

Validation and diagnostic skill for HASTE. Compare planned vs implemented work, generate diagnostic reports, and feed misses back into skill refinement. Use when: 'validate implementation', 'compare to spec', 'diagnostic report', 'drift analysis', 'coverage check', 'implementation review'.

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    When validation reveals a miss:

    line 107
  2. Distinctive:

    Document the miss in the diagnostic report

    line 108

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Validation & Diagnostics

Overview

Structured process for comparing planned vs implemented work, generating diagnostic reports, and identifying gaps. Used by validation agents to provide concrete, evidence-based assessments.

Key Concepts

The Trust Problem

Agents will claim work is complete when it isn't. Validation must be:

  • Observable — Based on test output, not agent claims
  • Deterministic — Same input produces same verdict
  • Evidence-based — Every finding references concrete code or test results
  • Structured — Consistent format for easy human review

Patterns & Techniques

Planned vs Implemented Comparison

Step 1: Extract planned items From the spec, issue, or plan, extract a checklist of:

  • Acceptance criteria
  • Required endpoints/functions
  • Expected model fields
  • Required test coverage
  • UI components specified

Step 2: Verify each item For each planned item, check:

  • Does the code exist? (file search, grep)
  • Does it match the specification? (read and compare)
  • Is it tested? (find corresponding test)
  • Does the test pass? (run and capture output)

Step 3: Generate drift report

## Drift Analysis: [Feature]

| Planned Item | Status | Evidence |
|-------------|--------|----------|
| [spec item] | ✅ Implemented | [file:line] |
| [spec item] | ⚠️ Partial | [what's missing] |
| [spec item] | ❌ Not found | [searched in...] |
| [unplanned] | ⚡ Scope creep | [file:line] |

Diagnostic Report Template

## Diagnostic Report: [Component/Feature]

### Summary
[1-2 sentence verdict]

### Test Results

[Actual test output — copy/paste, not paraphrased]


### Code Quality
| Metric | Result |
|--------|--------|
| Type hints present | ✅ / ❌ |
| Pydantic models used | ✅ / ❌ |
| Config class used (no hardcoded secrets) | ✅ / ❌ |
| Error handling present | ✅ / ❌ |
| Logger used (not print) | ✅ / ❌ |

### Findings
| # | Severity | Finding | Location | Recommendation |
|---|----------|---------|----------|----------------|
| 1 | [High/Med/Low] | [what] | [file:line] | [fix] |

### Coverage Gaps
[Code paths without tests]

### Verdict
✅ PASS | ⚠️ CONDITIONAL PASS | ❌ FAIL
[Explanation with evidence]

HASTE-Specific Validation Checks

ComponentMust Verify
New API endpointAuth level, Pydantic validation, error codes, CORS
New processorConfig injection, logger usage, error handling
New data modelPydantic BaseModel, field types, validation rules
New data layerAbstract interface compliance, connection handling
New UI componentFluentUI usage, no alt frameworks, responsive
Geospatial codeCRS preservation, COG compliance, GDAL/rasterio usage

Feedback Loop

When validation reveals a miss:

  1. Document the miss in the diagnostic report
  2. Identify the pattern (was it a convention violation? missing test? spec ambiguity?)
  3. Propose a skill update or instruction addition to prevent recurrence
  4. Flag to the Orchestrator for tracking

Decision Framework

Validation ResultAction
All checks pass, tests green✅ Approve
Minor issues, tests pass⚠️ Conditional — list issues for human review
Tests fail❌ Block — must fix before proceeding
Scope creep detected⚠️ Flag — human decides if extra work is acceptable
Spec ambiguity found⚠️ Flag — needs clarification before validation

Common Pitfalls

  • Accepting "tests passed" without seeing output — Always run and capture
  • Validating only happy path — Check error handling and edge cases
  • Skipping convention checks — HASTE has specific patterns that must be followed
  • Not checking for scope creep — Extra changes can introduce regressions

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