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/rduffyuk/qwen-memory-agent/agents-mdgit clone --depth 1 https://github.com/rduffyuk/qwen-memory-agentWrote 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/rduffyuk/qwen-memory-agent/agents-md)<a href="https://agentmods.dev/instructions/rduffyuk/qwen-memory-agent/agents-md"><img src="https://agentmods.dev/badge/instructions/rduffyuk/qwen-memory-agent/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 | $0.00462 | $0.00462 |
| Opus 5 | $0.00231 | $0.00231 |
| Sonnet 5 | $0.00092 | $0.00092 |
| Haiku 4.5 | $0.00046 | $0.00046 |
Grade A, and why
qwen-memory-agent 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 5d 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.
What it actually says
AGENTS.md — qwen-memory-agent
Fresh public repo (GitHub, MIT) for the Qwen Cloud Hackathon Track 1 entry. This is NOT the private Rootweaver platform — do not import, reference, or paste anything from it.
Hard rules
- Zero secrets in code. The DashScope API key lives ONLY in
.env(gitignored). Read it via env vars (DASHSCOPE_API_KEY,DASHSCOPE_BASE_URL). Never hardcode, log, or print the key. Provide a.env.examplewith placeholder values only. - Mock-first / zero-spend tests. Tests MUST NOT make live network calls to Qwen/DashScope. The Qwen client (
qwen.py) must be injectable/mockable so the whole engine + MCP + scorer are testable offline. Use Qdrant local in-memory mode (QdrantClient(location=":memory:")) in tests — no server, no Docker. - Don't weaken tests. Never delete, rename, skip, or
xfailan existing test or assertion. - Scope discipline. Implement only the gate spec. No unrelated refactors. Keep all runtime deps inside the already-declared
pyproject.tomlset; if you truly need another, add it to[project.dependencies]. - Format before finishing:
black+isort(configured inpyproject.toml, line-length 100).
Layout
src/memory_agent/ api.py · mcp_server.py · engine.py · qwen.py · store.py · models.py
benchmark/ generate.py · baselines.py · run.py · score.py · results/
tests/ unit tests (the gate: `pytest -q tests/`)
deploy/ ecs_setup.md · docker-compose.yml
Gate
pytest -q tests/ must pass, fully offline. Tests cover at minimum:
- supersession retires the prior fact of the same subject/type;
- budget-packing never exceeds the configured token limit;
- retrieve ranks a relevant memory above a distractor;
- the scorer computes recall + staleness correctly on a fixture.
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.
- 5d ago First seen · 27 lines · 462 tokens per session scan A 4b1783173166
qwen-memory-agent AGENTS.md is an instructions file published in the GitHub repository rduffyuk/qwen-memory-agent (0 stars, last pushed 1mo ago), licensed MIT. It adds 462 tokens to every session, about $0.0023 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
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).
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 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).
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.
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
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.