topos

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<h3 align="center">A structural quality gate for coding agents.</h3>

<p align="center">
  Topos measures complexity, coupling, and risky data flows, then gives your agent a concrete target&mdash;from SLOP to GOLD.
</p>

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  <a href="https://github.com/mcp/Krv-Labs/topos"><img src="https://img.shields.io/badge/VS_Code-Install_MCP-007ACC?logo=visualstudiocode&logoColor=white" alt="Install Topos MCP in VS Code"></a>
  <a href="https://pypi.org/project/topos-mcp/"><img src="https://img.shields.io/pypi/v/topos-mcp?color=3776AB&logo=python&logoColor=ffd43b" alt="PyPI"></a>
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<!-- mcp-name: io.github.Krv-Labs/topos -->

<p align="center">
  <a href="#install-and-quick-start">Install</a> ·
  <a href="#what-topos-checks">What it checks</a> ·
  <a href="#under-the-hood">Under the hood</a> ·
  <a href="https://docs.krv.ai/topos/">Docs</a> ·
  <a href="https://github.com/Krv-Labs/topos/issues">Issues</a>
</p>

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DEMO STUB — replace this comment only after recording the real release flow.

Show, in under 20 seconds:
1. an agent evaluates a repository;
2. Topos identifies the exact failing pillar and source hotspot;
3. the agent makes one focused refactor;
4. Topos verifies the medal improvement while the project tests stay green.

Prefer a checked-in, captioned GIF or SVG terminal recording with a stable
repository-relative URL. Do not publish a synthetic or hand-written result.
-->

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STUDY STUB — keep hidden until the study, raw results, pinned repository SHAs,
and reproduction method are public.

Candidate headline:
"We evaluated <N> public repositories at pinned commits. <result>."

Required link target: a durable methodology/results page containing the corpus
selection rule, Topos version and configuration, machine details, raw JSON,
known limitations, and a reproduction command. Avoid labeling repositories as
"AI-generated" unless that provenance is explicit and independently verifiable.
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## Why Topos

Coding agents produce working code quickly. The harder question is whether the result is still easy to understand, safe to change, and well-fitted to the rest of the repository. **[Quality is the new currency.](https://krv.ai/field-notes/evaluating-code-generation)**

Topos computes that signal from program structure—not from an LLM review or a style opinion—and returns concrete failure locations and next actions. It is fast enough to sit inside the agent loop: measure, edit, verify, repeat.

**Tests check behavior. Topos checks whether the implementation is built to keep changing.**

> Grounded in category theory, powered by a native-Rust engine.


## Under the hood

Topos is a self-contained Rust CLI and MCP server. Analysis runs locally; your source code is not sent to an external model or hosted analysis service.

| Component | Role |
| :--- | :--- |
| [tree-sitter](https://tree-sitter.github.io/tree-sitter/) | Parses six languages and powers the native AST, CFG, CPG, PDG, and UAST representations. |
| [GitNexus](https://github.com/abhigyanpatwari/GitNexus) | Supplies the repository dependency graph scored by COMPOSABLE (`topos depgraph generate`). Requires `npm install -g gitnexus@1.6.8`. |
| [Sighthound](https://github.com/Corgea/Sighthound) | Embedded in the MCP server for supplementary security findings; native CPG probes remain the SECURE scoring source. |
| [Graphify](https://github.com/Graphify-Labs/graphify) | Optional advisory orphan and fragile-edge detection via `topos graphify` / `topos_refactor(target="graphify")`; does not affect the medal. Requires `pip install graphifyy`. |

The result is one agent-facing contract over several structural lenses: one score to optimize, explicit evidence for each failure, and a verification loop that can tell a real improvement from cosmetic churn.

## Install and Quick Start

### VS Code MCP Extension

Open the Extensions view, search **`@mcp topos`**, select **Topos**, and choose **Install**. Or view here: [Topos: GitHub's MCP Registry](https://github.com/mcp/Krv-Labs/topos).

Then ask agent mode:

> Use Topos to fi

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