Borrowing it
Nothing to install: this file belongs to AbiyuLingga/LTSpice-MCP. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/AbiyuLingga/LTSpice-MCP/main/AGENTS.mdgit clone --depth 1 https://github.com/AbiyuLingga/LTSpice-MCPWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/abiyulingga/ltspice-mcp/agents-md)<a href="https://agentmods.dev/instructions/abiyulingga/ltspice-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/abiyulingga/ltspice-mcp/agents-md.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.04099 | $0.04099 |
| Opus 5 | $0.02049 | $0.02049 |
| Sonnet 5 | $0.00820 | $0.00820 |
| Haiku 4.5 | $0.00410 | $0.00410 |
Grade A, and why
LTSpice-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 6d ago.
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.
How it starts
The opening of the file, as written. The whole thing — 312 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Operational guide for AI coding agents working inside this repository.
This file is the canonical entry point. CLAUDE.md, OPENCODE.md, and
MCP.md are thin shims that point here.
What this project is
ltspice-ai-agent is a local Python CLI plus a local MCP server that
lets AI agents safely generate, simulate, inspect, and reuse LTspice
circuits. The Python core owns all validation, file generation, and
simulation execution. The agent proposes intent, parameters, and topology
only.
The active long-term plan lives in
docs/AI_HARDWARE_AGENT_ROADMAP.md.
docs/PROJECT_PLAN.md remains the historical analog
MVP plan. Phase 12 (Tiny8) is complete and the Phase 13 live-editing/Math
Core surface is an integrated prototype. New work follows the serialized
single-agent milestones in
docs/SINGLE_AGENT_EXECUTION_PLAN.md.
Phase 7 (Create Project Workflow) is complete. ltagent create takes
either an IR JSON file path or a natural-language prompt, runs the planner,
and writes the full project artefact set. Refusal paths return the
create.refused structured payload.
Phase 8 (Rule-Based Planner) is complete. ltagent plan "<prompt>"
parses a small, deterministic set of English and Indonesian prompts into a
validated CircuitIR. See src/ltagent/planner.py and the public API:
plan_prompt(text: str) -> CircuitIR | PlannerRefusal. The CLI subcommand
mirrors that. Do not introduce an LLM-backed planner before documenting
the contract change in an ADR; Phase 8 is intentionally rule-based.
Phase 9 (Template Evaluator / Promoter) is complete. Failed
simulation, low layout score, and duplicate value-only templates cannot
become official. Promotion is manual via ltagent template promote.
The evaluator records the score and gates from plan §15.3.
Phase 10 (MCP Server v1) is complete. ltagent-mcp (after
pip install "ltspice-ai-agent[mcp]") runs an stdio MCP server that
originally shipped 10 curated tools and 8 curated resources backed by the
same Python core. The current integrated surface exposes 27 tools and 16
resources. No run_shell, no execute_python, no generic
read_file/write_file, no .raw exposure. See MCP.md and
docs/mcp_setup.md.
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.
- 6d ago First seen · 312 lines · 4,099 tokens per session scan A 737db11bac94
LTSpice-MCP AGENTS.md is an instructions file published in the GitHub repository AbiyuLingga/LTSpice-MCP (0 stars, last pushed 2mo ago), licensed MIT. It adds 4,099 tokens to every session, about $0.0205 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.
Other instructions, from other repositories
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AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.