Invariant Analyzer Skill

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Identify and verify loop invariants for correctness proofs

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Details

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What this skill tells your AI

The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/algorithms-optimization/skills/invariant-analyzer/SKILL.md and read by Ahel’s review.

Purpose

Identify and verify loop invariants to help construct correctness proofs for algorithms.

Capabilities

  • Automatic loop invariant inference
  • Invariant verification against code
  • Precondition/postcondition extraction
  • Generate formal proof structure
  • Identify missing invariants

Target Processes

  • correctness-proof-testing
  • algorithm-implementation

Invariant Analysis Framework

Loop Invariant Properties

  1. Initialization: True before first iteration
  2. Maintenance: If true before iteration, true after
  3. Termination: Provides useful property at end

Common Invariant Patterns

  • Range invariants: "for all i in [0, k), property P(i) holds"
  • Accumulator invariants: "sum equals sum of a[0..k-1]"
  • Pointer invariants: "left < right and all elements < left are processed"
  • State invariants: "data structure maintains property X"

Input Schema

{
  "type": "object",
  "properties": {
    "code": { "type": "string" },
    "language": { "type": "string" },
    "loopIndex": { "type": "integer" },
    "expectedInvariant": { "type": "string" }
  },
  "required": ["code"]
}

Output Schema

{
  "type": "object",
  "properties": {
    "success": { "type": "boolean" },
    "invariants": { "type": "array" },
    "preconditions": { "type": "array" },
    "postconditions": { "type": "array" },
    "proofOutline": { "type": "string" }
  },
  "required": ["success"]
}

Signals

GitHub stars
2k
Forks
113
Last commit
Sep 2026
Advanced
Item type
skill
Key
invariant-analyzer
Source
github.com/a5c-ai/babysitter