invariant-analyzer
Identify and verify loop invariants for correctness proofs
npx skills add a5c-ai/babysitter --skill invariant-analyzer --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Invariant Analyzer Skill ## 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 ```json { "type": "object", "properties": { "code": { "type": "string" }, "language": { "type": "string" }, "loopIndex": { "type": "integer" }, "expectedInvariant": { "type": "string" } }, "required": ["code"] } ``` ## Output Schema ```json { "type": "object", "properties": { "succe
- Purpose
- Capabilities
- Target Processes
- Invariant Analysis Framework
- Loop Invariant Properties
- Common Invariant Patterns
- Input Schema
- Output Schema
What does the invariant-analyzer skill do?
Identify and verify loop invariants for correctness proofs
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill invariant-analyzer --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.