Borrowing it
Nothing to install: this file belongs to NicolasPrimeau/artel. 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/NicolasPrimeau/artel/master/CLAUDE.mdgit clone --depth 1 https://github.com/NicolasPrimeau/artelWrote 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/nicolasprimeau/artel/claude-md)<a href="https://agentmods.dev/instructions/nicolasprimeau/artel/claude-md"><img src="https://agentmods.dev/badge/instructions/nicolasprimeau/artel/claude-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 | $0.00737 | $0.00737 |
| Opus 5 | $0.00368 | $0.00368 |
| Sonnet 5 | $0.00147 | $0.00147 |
| Haiku 4.5 | $0.00074 | $0.00074 |
Grade A, and why
artel CLAUDE.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 8d 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Artel
A self-hosted, self-organizing mesh for AI agent fleets — shared memory, session continuity, agent-to-agent communication, cross-instance feed meshing, and async archival synthesis across machines and LLM providers.
What It Is
Artel is a self-hosted server that gives a fleet of AI agents a self-organizing shared memory and coordination layer that meshes across instances with no central coordinator. Any agent that can make HTTP calls can participate — Claude Code, AutoGen, raw API scripts, anything. Agents read and write memory, pass messages, claim tasks, and emit events. An async archivist agent watches all activity and synthesizes connections no individual agent can see.
Stack
- Python 3.11+ (CI tests 3.11/3.12/3.13), FastAPI, SQLite (WAL mode), sqlite-vec (embeddings)
- MCP adapter on top of core REST API
- Self-hosted, accessible from all machines
Layout
artel/
server/ — FastAPI app, routes, auth
store/ — SQLite models, migrations
archivist/ — async synthesis agent
mcp/ — MCP adapter over REST
scripts/
migration/ — DB migrations
docs/
plan.md — execution plan
spec.md — protocol and data model spec
architecture.md — system design
.claude/
memory/ — agent memory
skills/ — project skills
Core Primitives
- Memory — shared knowledge store with embeddings, confidence scores, provenance
- Tasks — create/claim/complete units of work across agents
- Messages — direct agent-to-agent async inbox
- Events — pub/sub stream for real-time coordination
Agent Identity
API key + agent_id string. No framework coupling. Any HTTP client participates.
Conventions
- Conventional commits (feat:, fix:, refactor:, docs:)
- No secrets in files — env vars only
- No comments or docstrings
- Pydantic models, no hardcoded strings
Documentation style
Concise but flowing. Prose that connects, not bullets that stack.
- Say a thing once. The archivist's merge/decay/promote list was once spelled out four times in near-identical words across the hero, a feature bullet, and two adjacent paragraphs of its own section. Detail belongs in the section that owns it; everywhere else points at that section.
- Lead with what it does for the reader, then how it works. A section opening on its own internals assumes a reader who already knows why they are there.
- Paragraphs over fragments. A bullet list is right for genuinely parallel items and wrong for an argument — if the bullets need to be read in order, they are a paragraph.
- Cut the throat-clearing. "It is worth noting that", "in order to", a sentence restating the heading. If a sentence survives deletion unmissed, delete it.
- Reference pages are generated (
scripts/gen_docs.py) — never hand-write what a docstring, the OpenAPI schema, or a Settings class already states. - New primitives need prose, not just docstrings:
scripts/check_docs.pyfails until a page claims the surface with<!-- covers: name -->.
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.
- 8d ago First seen · 78 lines · 737 tokens per session scan A a660702ced73
artel CLAUDE.md is an instructions file published in the GitHub repository NicolasPrimeau/artel (8 stars, last pushed 4d ago), licensed MIT. It adds 737 tokens to every session, about $0.0037 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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