schematic-mcp AGENTS.md

Repository instructions for schematic-mcp, a server that gives AI agents structured context from electronic schematics.

In plain words
What is it for?
Guiding work on schematic parsers, the shared component-and-connection model, graph queries, workspace boundaries, MCP tools, examples, and tests.
Why use it?
They define the project's goal, architecture, development loop, and electrical-correctness requirements so changes fit the existing design.

Instructions file for CodexOpenCode

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add instructions/vonpanda/schematic-mcp/agents-md
Clone the repo
git clone --depth 1 https://github.com/vonpanda/schematic-mcp

Made for: Codex, OpenCode.

Per session 911 This file is loaded in full into every session.
When invoked 911 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00911 $0.00911
Opus 5 $0.00456 $0.00456
Sonnet 5 $0.00182 $0.00182
Haiku 4.5 $0.00091 $0.00091

Measured yesterday against content hash dd1eadb22a9c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

schematic-mcp AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

AGENTS.md · 95 lines

How it starts

The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

This file gives coding agents and human contributors the project rules that matter most when changing schematic-mcp.

Project goal

schematic-mcp is a hardware-context server for AI agents. It converts EDA schematics into a deterministic, format-neutral component/pin/net model and exposes that model through MCP.

The project is not trying to become a general-purpose KiCad GUI automation layer or an autorouter. The long-term direction is read-oriented hardware context, cross-EDA adapters, electrical reasoning, and firmware ↔ schematic validation.

Architecture

  • src/schematic_mcp/parsers/ — EDA-specific adapters. New formats should terminate in the canonical model rather than leak format-specific behavior into MCP tools.
  • src/schematic_mcp/models.py — canonical data structures.
  • src/schematic_mcp/graph.py — deterministic graph/query helpers over the canonical model.
  • src/schematic_mcp/workspace.py — current loaded schematic and filesystem boundary enforcement.
  • src/schematic_mcp/server.py — MCP tools/resources and CLI transport setup.
  • examples/ — synthetic or explicitly redistributable fixtures only.
  • tests/ — behavior and regression tests.

Read docs/architecture.md before making parser/model changes.

Required development loop

From a clean checkout:

python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"
pytest
python -m build

On Windows, use the appropriate virtual-environment activation command instead of source.

Every behavior change should add or update tests. Parser bugs should be reduced to the smallest safe fixture that reproduces the issue.

Electrical correctness invariants

  1. Never invent connectivity. If the file does not provide enough information to resolve a connection, preserve an unknown state or emit a warning.
  2. Do not infer internal IC connectivity. trace_signal follows resolved schematic nets only.
  3. Keep parser behavior deterministic. The same file should produce the same canonical model without an LLM call.
  4. Preserve ambiguity. Duplicate labels, ambiguous pin names, unsupported constructs, and unresolved hierarchy should be surfaced explicitly rather than silently normalized away.
  5. Prefer exact source evidence. When adding future confidence-based adapters such as PDF parsing, attach confidence/source metadata rather than presenting uncertain results as exact net connectivity.

Read the full file on GitHub · 95 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 95 lines · 911 tokens per session scan A dd1eadb22a9c

Subscribe to this mod's changes

schematic-mcp AGENTS.md is an instructions file published in the GitHub repository vonpanda/schematic-mcp (0 stars, last pushed 14d ago), licensed Apache-2.0. It adds 911 tokens to every session, about $0.0046 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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