What is ensemble AGENTS.md?

A set of AGENTS.md instructions for Ensemble, a local Python server that gives coding agents shared memory, codebase indexing, model routing, and other tools.

Use it when working on Ensemble: install or register its MCP server, add agent or skill files, start its local dashboard, run tests, lint, type checks, or build the package.

It tells agents how the project is organised, which commands are available, and how to run checks without sending requests to language-model APIs.

How LynkByte/ensemble configures Codex and OpenCode

Reuse

Borrowing it

Nothing to install: this file belongs to LynkByte/ensemble. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/LynkByte/ensemble/main/AGENTS.md

Clone the repo

git clone --depth 1 https://github.com/LynkByte/ensemble

Made for: Codex, OpenCode.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/instructions/lynkbyte/ensemble/agents-md/github.svg)](https://agentmods.dev/instructions/lynkbyte/ensemble/agents-md)

Your own site

<a href="https://agentmods.dev/instructions/lynkbyte/ensemble/agents-md"><img src="https://agentmods.dev/badge/instructions/lynkbyte/ensemble/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/instructions/lynkbyte/ensemble/agents-md"><img src="https://agentmods.dev/badge/instructions/lynkbyte/ensemble/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 1,001 This file is loaded in full into every session.

When invoked 1,001 The same file — it is already loaded in full.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

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.

Model	Per session	Once invoked
Fable 5.1	$0.01001	$0.01001
Opus 5.5	$0.00400	$0.00400
Sonnet 5.5	$0.00200	$0.00200
Haiku 4.5	$0.00100	$0.00100

Measured 2mo ago against content hash b95da61ca934, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ensemble 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 2mo 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.

AGENTS.md · 77 lines

How it starts

The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

Overview

Python MCP server (ensemble-mcp) providing vector memory, drift detection, model routing, skills discovery, session management, codebase indexing, context compression, prompt caching, and a local web dashboard. Fully implemented — 19 MCP tools across 11 subpackages, CLI with serve/install/uninstall/add-agents/add-skills/web commands.

Commands

pip install -e .                  # editable install
ensemble-mcp                      # run server (or: python -m ensemble_mcp)
ensemble-mcp install              # auto-detect AI tools and register MCP
ensemble-mcp uninstall            # remove MCP registration from AI tool configs
ensemble-mcp add-agents           # copy agent files (no MCP registration)
ensemble-mcp add-skills           # copy skill files (no MCP registration)
ensemble-mcp web                  # launch web dashboard at localhost:8787
ensemble-mcp web --port 9000      # custom port
ensemble-mcp web --no-open        # start without auto-opening browser
python -m pytest tests/           # run tests
ruff check src/ tests/            # lint
ruff format src/ tests/           # format
mypy src/                         # typecheck
python -m build                   # build sdist + wheel
docker build -t ensemble-mcp .    # build container

ruff and mypy are fully configured in pyproject.toml (strict mode, Python 3.11 target).

Architecture

src layout — package lives at src/ensemble_mcp/, mapped via [tool.hatch.build.targets.wheel].

Entry point: __main__.py → server.serve() (stdio MCP server).

Subpackage	Role
`config/`	Layered settings, defaults
`contracts/`	Response envelope and error taxonomy
`memory/`	ONNX embeddings, SQLite vector store, cosine similarity
`security/`	Secret redaction, trust boundary enforcement
`state/`	Session/step lifecycle, idempotency, locks
`tools/`	19 MCP tool implementations + call-recording utility (8 categories below)
`installer/`	Auto-detect AI tools, register MCP server
`dashboard/`	Web dashboard: aiohttp server, JSON API, Alpine.js SPA
`compress/`	Rule-based text compression engine
`cli/`	Startup banner
`data/`	Bundled agent and skill files

Read the full file on GitHub · 77 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.

2mo ago First seen · 77 lines · 1,001 tokens per session scan A b95da61ca934

Subscribe to this mod's changes

ensemble AGENTS.md is an instructions file published in the GitHub repository LynkByte/ensemble (1 stars, last pushed 3mo ago), licensed MIT. It adds 1,001 tokens to every session, about $0.0040 per session on Opus 5.5. 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.

Building agents Memory and context

ensemble AGENTS.md next to 6 instructions from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
ensemble AGENTS.mdLynkByte/ensemble	Instructions file	1	3mo ago	MIT	A	1,001	Codex, OpenCode
vscode buildNext.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	9,719	GitHub Copilot
next.js AGENTS.mdvercel/next.js	Instructions file	143k	yesterday	MIT	A	7,461	Codex, OpenCode
langchain AGENTS.mdlangchain-ai/langchain	Instructions file	149k	yesterday	MIT	A	4,680	Codex, OpenCode
vscode oss-third-party-notices.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	5,516	GitHub Copilot
vscode copilot-instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	3,093	GitHub Copilot
deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness	Instructions file	274k	2d ago	MIT	A	4,313	Codex, OpenCode

ensemble: Instructions file for Codex