What is mistral-managed-queue AGENTS.md?

Repository-specific instructions for a Python MCP server and command-line tool that queues Mistral API requests in SQLite. Rate limiting means it deliberately spaces requests to comply with service limits.

Use them when working on the queue database, Mistral API wrapper, worker commands, configuration, or tests. They document commands for submitting, fetching, processing, watching, and purging tasks.

They explain the project structure and prevent changes that could break task claiming, retries, rate limits, or concurrent queue processing.

How utenadev/mistral-managed-queue configures Codex and OpenCode

Reuse

Borrowing it

Nothing to install: this file belongs to utenadev/mistral-managed-queue. 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/utenadev/mistral-managed-queue/main/AGENTS.md

Clone the repo

git clone --depth 1 https://github.com/utenadev/mistral-managed-queue

Made for: Codex, OpenCode.

Wrote this? Show the measurements

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README.md

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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

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Per session 2,121 This file is loaded in full into every session.

When invoked 2,121 The same file — it is already loaded in full.

Security scan B 1 finding. 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	$0.02121	$0.02121
Opus 5.5	$0.00848	$0.00848
Sonnet 5.5	$0.00424	$0.00424
Haiku 4.5	$0.00212	$0.00212

Measured 2mo ago against content hash e8c28ff86c3a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade B, and why

mistral-managed-queue AGENTS.md scanned grade B 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 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.

Asks the agent to reveal its instructionsmediumSystem prompt leakage

Directions to print, repeat or translate the system prompt extract configuration the operator did not intend to expose.

| `MMQ_FAKE_RESPONSE` | — | Fixed fake response text (else echo prompt) |

AGENTS.md · 140 lines

How it starts

The opening of the file, as written. The whole thing — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

Project

mistral-managed-queue — Python MCP server + CLI that queues Mistral API calls with rate limiting (free-tier ~1 req/30s) via SQLite (WAL mode). Package layout under mmq/. Console script: mmq (mmq.cli:main).

Architecture

mmq/config.py — all constants + env-var defaults (wait times, model, DB timeouts).
mmq/db.py — SQLite layer: init_db, task lifecycle (register_task, claim_task, claim_next_task, get_task, touch_task, update_task_status), rate-limit gate (wait_for_rate_limit), purge_tasks, read_queue_status. Task claiming uses SQLite UPDATE ... RETURNING (needs SQLite >= 3.35).
mmq/core.py — Mistral wrapper (call_mistral_api with retries + shared gate), FakeMistralClient (offline e2e), queue execution:
- execute_mistral_queue_async(req) — self-serve path (MCP): registers its own task and claims only its own (avoids cross-claim deadlock; see tests TestExecuteQueueConcurrent).
- execute_next_task_async / drain_queue_async / watch_queue_async — the mmq work worker, which claims pending tasks by priority (DESC) then FIFO.
mmq/cli.py — subcommands: ask, fetch, work, purge, catalog fetch, mcp, --mcp.
mmq/mcp_server.py — FastMCP server; tools ask_mistral, get_queue_status.
mmq/README_MCP.md — MCP host setup (opt-in; ja/fr siblings alongside).
mmq/catalog/ — ORR-compatible catalog fetch/validate/write (fetch.py, validate.py, write.py, types.py). write_catalog_yaml(path, document) (order matters). Feature docs: mmq/catalog/README.md (ja/fr siblings).
mmq/__init__.py — __version__ + re-exports. Version is kept in sync with pyproject.toml (currently 0.2.2).

Key Concepts

Rate gate: single shared row in SQLite; every API attempt (first included) waits on it, so all processes/CLI/MCP are uniformly throttled. 429s raise the shared backoff.
Self-serve vs worker: MCP ask_mistral processes its own request inline. mmq fetch only enqueues; mmq work (worker mode) drains the queue by priority.
Fake API: MMQ_FAKE_API=1 uses FakeMistralClient (echoes prompt unless MMQ_FAKE_RESPONSE set). MMQ_FAKE_FAIL=429|error simulates failures.

Read the full file on GitHub · 140 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 · 140 lines · 2,121 tokens per session scan B e8c28ff86c3a

Subscribe to this mod's changes

mistral-managed-queue AGENTS.md is an instructions file published in the GitHub repository utenadev/mistral-managed-queue (0 stars, last pushed 2mo ago), licensed MIT. It adds 2,121 tokens to every session, about $0.0085 per session on Opus 5.5. A static security scan graded it B with 1 finding (asks the agent to reveal its instructions). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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mistral-managed-queue: Instructions file for Codex