# Algorithm Correctness Invariants

> Validates algorithm correctness using invariants, preconditions, and postconditions.

- **Type:** Skill
- **Install:** `agentstack add skill-jonatangs777-ai-skill-agent-control-deck-2026-algorithm-correctness-invariants`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [JonatanGS777](https://agentstack.voostack.com/s/jonatangs777)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [JonatanGS777](https://github.com/JonatanGS777)
- **Source:** https://github.com/JonatanGS777/ai-skill-agent-control-deck-2026/tree/main/skills/algorithm-correctness-invariants
- **Website:** https://github.com/JonatanGS777/ai-skill-agent-control-deck-2026

## Install

```sh
agentstack add skill-jonatangs777-ai-skill-agent-control-deck-2026-algorithm-correctness-invariants
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Algorithm Correctness Invariants Skill

## Mission
Validates algorithm correctness using invariants, preconditions, and postconditions.

## When to use
- When the task requires strict logical correctness and defensible reasoning.
- When assumptions, constraints, and proof obligations must be made explicit.

## Inputs expected
- Formal problem statement, constraints, and success criteria.
- Known assumptions, unknowns, and boundary conditions.

## Workflow
1. Translate the task into formal entities, assumptions, and constraints.
2. Derive the solution through explicit logical rules or proof structure.
3. Validate with edge cases, contradiction checks, and consistency tests.

## Output contract
Return: formal framing, reasoning chain, verification evidence, and residual uncertainty.

## Guardrails
- Never skip logical steps or present intuition as proof.
- Never mix assumptions with verified facts.
- Always provide at least one explicit validation or counterexample check.

## Logical reliability checklist
- Assumptions are explicit and separated from verified facts.
- The solution path is justified with clear reasoning steps.
- Edge cases and contradiction checks are included.
- Output is testable, auditable, and reversible when possible.

## Example prompts
- "Apply the algorithm-correctness-invariants skill to handle this task end-to-end."
- "Run algorithm-correctness-invariants and produce a production-ready output with validation notes."

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [JonatanGS777](https://github.com/JonatanGS777)
- **Source:** [JonatanGS777/ai-skill-agent-control-deck-2026](https://github.com/JonatanGS777/ai-skill-agent-control-deck-2026)
- **License:** MIT
- **Homepage:** https://github.com/JonatanGS777/ai-skill-agent-control-deck-2026

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-jonatangs777-ai-skill-agent-control-deck-2026-algorithm-correctness-invariants
- Seller: https://agentstack.voostack.com/s/jonatangs777
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.