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/gatordevin/avo/agents-mdgit clone --depth 1 https://github.com/gatordevin/avoWrote 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/gatordevin/avo/agents-md)<a href="https://agentmods.dev/instructions/gatordevin/avo/agents-md"><img src="https://agentmods.dev/badge/instructions/gatordevin/avo/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 | $0.01178 | $0.01178 |
| Opus 5 | $0.00589 | $0.00589 |
| Sonnet 5 | $0.00236 | $0.00236 |
| Haiku 4.5 | $0.00118 | $0.00118 |
Grade A, and why
avo 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 3d 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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — instructions for coding agents working in this repo
This file is read automatically by Codex CLI and other agents that follow the
AGENTS.md convention. Claude Code users additionally have a /avo skill in
.claude/skills/avo/.
There are two distinct things an agent does here, and they need different rules.
A. Working on the AVO codebase
Ordinary software work: fixing bugs, adding targets, adding backends.
python3 -m venv --system-site-packages .venv # if Python is externally managed
.venv/bin/pip install -e ".[dev]"
.venv/bin/pytest -q # 48 tests, no model or network needed
.venv/bin/avo doctor
Conventions:
- No mandatory dependencies beyond PyYAML. Anything else goes in an extra
and is imported lazily, so
avo doctorcan report what is missing rather than the import failing. - The framework never calls a model. Session mode is the default precisely because it costs nothing. Keep it that way.
- Prompts are the framework/agent interface.
src/avo/prompts.pychanges behaviour more than most code does. If you edit it, say in the commit message what you expect the operator to do differently. - Test anything touching the commit policy, the correctness gate, or the lineage. Those three are what make results trustworthy.
docs/PAPER_MAP.mdmaps every section of the paper to the code. If you change something it describes, update it.
B. Acting as the variation operator
This is the interesting one. You are the Agent in Vary(P_t) = Agent(P_t, K, f):
AVO owns the lineage, the scoring, and the commit policy; you own the thinking.
Use the avo_* MCP tools if they are available, otherwise the CLI — the
operations are identical. Full protocol in docs/DRIVING.md.
The loop
avo_start_run/avo start --target <name> --max-steps Navo_next_step/avo prompt— read it properly, it changes every step- Edit files under
work/; readkb/when you need it avo_evaluate/./avo-eval— as often as you like, it does not touch the lineageavo_submit -m "what changed and its measured effect"- On a reported stall:
avo_supervisor_brief, answer it yourself, thenavo_record_supervisor - Repeat, then
avo_plot
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.
- 3d ago First seen · 107 lines · 1,178 tokens per session scan A f2fc7a7bd74b
avo AGENTS.md is an instructions file published in the GitHub repository gatordevin/avo (6 stars, last pushed 12d ago), licensed Apache-2.0. It adds 1,178 tokens to every session, about $0.0059 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
ontology-atlas AGENTS.md
Instructions for wlsdks/ontology-atlas, covering agents.md — ontology-atlas, product and non-negotiable architecture, start here, structure and routes and operating gates and skills.
matt-skills-with-to-goal CLAUDE.md
Instructions for tt-a1i/matt-skills-with-to-goal: Skills are organized into bucket folders under skills/.
ephemeral-sandbox CLAUDE.md
Instructions for Ephemeral-AI-Lab/ephemeral-sandbox, covering claude.md, project, engineering practice (required), build & test and sandbox tools.
coral CLAUDE.md
Instructions for cdknorow/coral, covering claude.md - coral go, mission, testing, go unit tests and legacy parity tools (historical reference).
pixir CLAUDE.md
Instructions for Ranvier-Technologies/pixir, covering pixir harness - legacy agent guide, current map and commands.
Agent-Memory-Bridge AGENTS.md
Instructions for zzhang82/Agent-Memory-Bridge, covering agent memory bridge contributor instructions, setup and checks, architecture boundaries, mutation and migration invariants and benchmark expectations.