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.
npx agentmods add instructions/seattleuser0/autosage/agents-mdgit clone --depth 1 https://github.com/SeattleUser0/AutoSageWrote 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/seattleuser0/autosage/agents-md)<a href="https://agentmods.dev/instructions/seattleuser0/autosage/agents-md"><img src="https://agentmods.dev/badge/instructions/seattleuser0/autosage/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 | $0.00619 | $0.00619 |
| Opus 5 | $0.00309 | $0.00309 |
| Sonnet 5 | $0.00124 | $0.00124 |
| Haiku 4.5 | $0.00062 | $0.00062 |
Grade A, and why
AutoSage AGENTS.md scanned grade A with 1 finding 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 3d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- curl examples for `/healthz`, `/v1/responses`, `/v1/chat/completions` How it starts
The opening of the file, as written. The whole thing — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AutoSage — Agent Instructions
AutoSage is a backend toolkit that exposes an OpenAI-compatible HTTP interface so an AI agent (e.g., Open Claw) can run science/engineering solvers (FEA/CFD/circuits) through tool calls.
Non-negotiables
- Repository license: MIT.
- Only allow permissive third-party licenses in-tree: MIT, BSD-2/3, Apache-2.0, ISC, zlib.
- Do not add GPL/LGPL/AGPL dependencies or code.
- Must build cleanly via Swift Package Manager and open/build in Xcode.
Architecture
- Swift Package with these targets:
AutoSageCore(library): shared types and tool system.AutoSageServer(executable): HTTP server.
- Keep solver implementations behind a narrow interface so they can be swapped/refactored later.
- All externally visible behavior must be deterministic and size-bounded.
HTTP API (compatibility surface)
Implement and keep stable:
GET /healthz→ 200 with minimal JSON (status/version)POST /v1/responses→ OpenAI Responses-like JSONPOST /v1/chat/completions→ Chat Completions-like JSON
Defaults:
- Bind to
127.0.0.1:8080unless configured otherwise. - Content-Type
application/json.
Tool system
AutoSage supports tool calls. Provide a registry that maps tool name → implementation.
Initial tools (stubs are OK):
fea.solvecfd.solvecircuits.simulate
Tool contract:
- Each tool has:
name,description,jsonSchema(parameters),run(input) -> output. - Tool outputs must include:
status(e.g., "ok" / "error")solver(string identifier)summary(short human-readable)- Optional arrays must be capped/truncated (never return huge payloads).
Testing requirements
- Add unit tests for JSON decoding/encoding of request/response types.
- Add at least one handler smoke test per endpoint (request in → response shape out).
swift testmust pass.
Docs and notices
- Add
README.mdwith:- how to build/run the server
- curl examples for
/healthz,/v1/responses,/v1/chat/completions - tool-call example for one tool
- Add
THIRD_PARTY_NOTICES.md(even if empty initially). - If any third-party code is added later, its license text must be included and referenced.
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.
- 3d ago First seen · 62 lines · 619 tokens per session scan A 3b4d2cdac92b
AutoSage AGENTS.md is an instructions file published in the GitHub repository SeattleUser0/AutoSage (2 stars, last pushed 6mo ago), licensed MIT. It adds 619 tokens to every session, about $0.0031 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other instructions, from other repositories
cad-cae-copilot AGENTS.md
Instructions for armpro24-blip/cad-cae-copilot, covering aieng workbench — agent guide, stop — read this first, first three calls every session, workflow priority matrix and workspace layout.
cad-cae-copilot copilot-instructions.md
Instructions for armpro24-blip/cad-cae-copilot, covering github copilot — aieng workspace and essentials.
cad-cae-copilot CLAUDE.md
Instructions for armpro24-blip/cad-cae-copilot, covering claude code — aieng workspace and tl;dr.
circuit-synth CLAUDE.md
Instructions for circuit-synth/circuit-synth, covering claude.md - circuit-synth library development guide, project context, professional quality standards, 🎯 core development philosophy and 1. github issue-driven development.
IntentForge AGENTS.md
Instructions for jzjzzzzzzz/IntentForge, covering agent instructions, current phase, engineering rules and cad rules.
techdrawai-skills CLAUDE.md
Claude Code instructions for MeltFlexDevs/techdrawai-skills, covering notes for agents working in this repository, layout and rules.