# calma

> calma — rikhinkavuru-calma. Use this tool when you need to ensure accuracy and reliability in AI-computed results, as it provides a deterministic guardrail to re-run and recompute numbers, blocking incorrect outputs before they are shipped. It integrates with CLI, Claude Code hook, and MCP, allowing for seamless verification of AI-generated results. Ideal for use cases where precision is crucial, such as data-driven decision-making or automated workflows.

Canonical page: https://skillsregistry.net/skills/rikhinkavuru-calma  
JSON: https://api.skillsregistry.net/v1/skills/rikhinkavuru-calma

## Description

Re-run the work, recompute the number, block the wrong one before it ships — a deterministic guardrail for AI-computed results. CLI · Claude Code hook · MCP.

## Trust

- **Trust score (0–1):** 0.46
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/rikhinkavuru/calma)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "rikhinkavuru-calma"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/rikhinkavuru-calma` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/rikhinkavuru-calma/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt