Borrowing it
Nothing to install: this file belongs to hermes-labs-ai/zer0dex. 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/hermes-labs-ai/zer0dex/main/AGENTS.mdgit clone --depth 1 https://github.com/hermes-labs-ai/zer0dexWrote 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/hermes-labs-ai/zer0dex/agents-md)<a href="https://agentmods.dev/instructions/hermes-labs-ai/zer0dex/agents-md"><img src="https://agentmods.dev/badge/instructions/hermes-labs-ai/zer0dex/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/hermes-labs-ai/zer0dex/agents-md"><img src="https://agentmods.dev/badge/instructions/hermes-labs-ai/zer0dex/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 | $0.00308 | $0.00308 |
| Opus 5.5 | $0.00123 | $0.00123 |
| Sonnet 5.5 | $0.00062 | $0.00062 |
| Haiku 4.5 | $0.00031 | $0.00031 |
Grade A, and why
zer0dex 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.
What it actually says
AGENTS.md
zer0dex is a local dual-layer memory architecture for AI agents.
Use it for
- giving agents a compressed markdown memory index plus semantic retrieval
- seeding local memory from markdown or notes
- querying memory through a local HTTP server before each agent message
Do not use it for
- hosted memory infrastructure
- compliance or governance controls
- assuming benchmark numbers transfer unchanged to every domain
Minimal commands
pip install -e ".[dev]"
zer0dex --help
zer0dex init
python -m pytest tests/ -q
Output shape
zer0dex check: prerequisite validation with pass/fail lineszer0dex seed: chunk and memory-count progresszer0dex query: scored memory matcheszer0dex status: health plus memory count
Success means
- local setup, seeding, serving, and querying all work from the CLI
- tests pass offline with mocked dependencies
- the README quick-start flow matches the actual CLI commands
Common failure cases
- Ollama or required local models are not installed
- users treat the compressed index as full memory instead of a navigation layer
- teams expect zero tuning across very different memory workloads
Maintainer notes
- keep benchmark claims tied to the published evaluation docs
- keep the architecture framed as a local pattern and implementation, not a universal memory guarantee
- do not commit local store directories or secrets
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 · 50 lines · 308 tokens per session scan A b1119be34be9
zer0dex AGENTS.md is an instructions file published in the GitHub repository hermes-labs-ai/zer0dex (64 stars, last pushed 18d ago), licensed Apache-2.0. It adds 308 tokens to every session, about $0.0012 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 2026-08-30.
zer0dex AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| zer0dex AGENTS.mdhermes-labs-ai/zer0dex | Instructions file | 64 | 18d ago | Apache-2.0 | A | 308 | 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 | today | 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 |