# code-reason

> Use this tool when you need to analyze code programmatically, as it provides coding agents with program-analysis primitives such as data flow, call graphs, and taint analysis to reason about code accurately. It solves problems of unreliable code analysis and guesswork by providing ground truth insights, and accepts Git repositories as input. It outputs actionable data for informed coding decisions, making it ideal for use cases requiring precise code understanding.

Canonical page: https://skillsregistry.net/skills/blindhacker99-code-reason  
JSON: https://api.skillsregistry.net/v1/skills/blindhacker99-code-reason

## Description

MCP server that gives coding agents program-analysis primitives — data flow, call graphs, taint analysis — so they reason from ground truth instead of grep-and-guess."

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** other
- **Updated:** 2026-09-01

## Source

- **Source listing:** [GitHub](https://github.com/blindhacker99/code-reason)

## 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": "blindhacker99-code-reason"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/blindhacker99-code-reason` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/blindhacker99-code-reason/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