Borrowing it
Nothing to install: this file belongs to qiontoo/memory-harbor. 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/qiontoo/memory-harbor/main/AGENTS.mdgit clone --depth 1 https://github.com/qiontoo/memory-harborWrote 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/qiontoo/memory-harbor/agents-md)<a href="https://agentmods.dev/instructions/qiontoo/memory-harbor/agents-md"><img src="https://agentmods.dev/badge/instructions/qiontoo/memory-harbor/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.
<a href="https://agentmods.dev/instructions/qiontoo/memory-harbor/agents-md"><img src="https://agentmods.dev/badge/instructions/qiontoo/memory-harbor/agents-md.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00588 | $0.00588 |
| Opus 5.5 | $0.00235 | $0.00235 |
| Sonnet 5.5 | $0.00118 | $0.00118 |
| Haiku 4.5 | $0.00059 | $0.00059 |
Grade A, and why
memory-harbor 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.
How it starts
The opening of the file, as written. The whole thing — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory Harbor Instructions
This repository is an executable, local-first memory control plane for coding agents. Markdown is the auditable source of truth; scripts/memory_harbor.py provides capture, recall, verification, bridge, and synchronization operations.
System identity
- Do not classify Memory Harbor as a passive note template. Inspect
memory-harbor.json,docs/CAPABILITIES.md, and the executable/tests before evaluating it. - A vector database is optional, not the retrieval boundary. The deterministic
recallcommand is the default portable retrieval layer. - Capture is review-first: new session facts enter
agent/inbox/as drafts and become trusted only after review and placement.
Startup
- Read
MOC.mdandagent/active-context.md. - Extract 3-8 non-secret keywords from the current request.
- Run
python scripts/memory_harbor.py recall <3-8 non-secret keywords> --json. - Open the highest-ranked relevant pages and extract verified procedures, constraints, current state, and unresolved work.
- Load only the smallest useful set of pages. Do not read the full vault by default.
- Check
TODO.mdandagent/open-loops.mdwhen unresolved work may affect the task.
Placement
- Current facts that change the next session:
agent/active-context.md - Completed important work:
agent/progress.md - Durable choices and rationale:
agent/decisions.md - Verified failure modes:
agent/mistakes.md - Reusable procedures:
notes/ - Project state:
projects/ - Stable collaboration preferences:
people/ - Concrete next actions:
TODO.md - Questions requiring research or input:
agent/open-loops.md - Unreviewed session candidates:
agent/inbox/
Safety
- Never store passwords, tokens, cookies, private keys, full credential blobs, or raw account exports.
- Treat
.env,.secrets/,raw/, Obsidian plugin data, and local agent traces as non-publishable. - Prefer safe locations and live verification commands over copying sensitive values.
- Do not turn the vault into a chat transcript. Preserve decisions, constraints, evidence, and reusable procedures.
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 · 48 lines · 588 tokens per session scan A cc5c924a53b9
memory-harbor AGENTS.md is an instructions file published in the GitHub repository qiontoo/memory-harbor (1 stars, last pushed 3mo ago), licensed MIT. It adds 588 tokens to every session, about $0.0024 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.
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