# silicon_truth_bridge

> silicon_truth_bridge — nomatic163-silicon-truth-bridge. Use this tool when you need to verify chip designs and debug RTL without modifying the original databases. The silicon_truth_bridge provides read-only access to structured design and waveform data, solving problems related to chip verification and debugging by exposing auditable evidence through MCP tools and CLI. It is ideal for use cases requiring trustworthy and unaltered design data, such as auditing and troubleshooting chip designs.

Canonical page: https://skillsregistry.net/skills/nomatic163-silicon-truth-bridge  
JSON: https://api.skillsregistry.net/v1/skills/nomatic163-silicon-truth-bridge

## Description

A read-only MCP evidence server for chip verification and RTL debugging that exposes structured design and waveform data from Synopsys Verdi databases via MCP tools and CLI. It provides auditable evidence like contexts, objects, connectivity, traces, waveforms, and source mappings without modifying RTL or design DBs.

## Trust

- **Trust score (0–1):** 0.67
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/ocuc911rj6)
- **Repository:** <https://github.com/nomatic163/silicon_truth_bridge>

## 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": "nomatic163-silicon-truth-bridge"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/nomatic163-silicon-truth-bridge` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/nomatic163-silicon-truth-bridge/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