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 commands/valory-xyz/open-autonomy/autonomy_deploygit clone --depth 1 https://github.com/valory-xyz/open-autonomyWrote 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/commands/valory-xyz/open-autonomy/autonomy_deploy)<a href="https://agentmods.dev/commands/valory-xyz/open-autonomy/autonomy_deploy"><img src="https://agentmods.dev/badge/commands/valory-xyz/open-autonomy/autonomy_deploy.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 | $0.00000 | $0.02475 |
| Opus 5 | $0.00000 | $0.01238 |
| Sonnet 5 | $0.00000 | $0.00495 |
| Haiku 4.5 | $0.00000 | $0.00248 |
Grade A, and why
autonomy_deploy 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 4d 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 — 361 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Build or run AI agent deployments.
This command group consists of a number of functionalities for building AI agent deployments, run locally stored AI agent deployments, and run AI agent deployments defined in the on-chain protocol. See the appropriate subcommands for more information.
Options
--env-file FILE
: File containing environment variable mappings
Examples
If you have an .env file in the working directory, autonomy deploy will load the .env file automatically. If the file is not present in the working directory you can provide the path to the file using --env-file flag
autonomy deploy --env-file <path_to_dotenv> COMMAND [ARGS]
For loading the environment variables you can use a json file as well. While using a json file you can either use json serialized strings like
{
"ALL_PARTICIPANTS": "[\"0x0000000000000000000000000000000000000000\"]"
}
Or the json objects
{
"ALL_PARTICIPANTS": ["0x0000000000000000000000000000000000000000"]
}
The framework will handle both of these cases automatically.
autonomy deploy --env-file <path_to_json> COMMAND [ARGS]
autonomy deploy build
Build an AI agent deployment.
This command must be executed within a service folder. That is, a folder containing the AI agent configuration file (service.yaml). The deployment will be created in the subfolder ./abci_build_*.
Usage
autonomy deploy build [OPTIONS] [KEYS_FILE]
Options
--o PATH
: Path to output directory.
--n INTEGER
: Number of agent instances.
--docker
: Use docker as a backend.
--kubernetes
: Use kubernetes as a backend.
--dev
: Create development environment.
--log-level [INFO|DEBUG|WARNING|ERROR|CRITICAL]
: Logging level for runtime.
--packages-dir PATH
: Path to packages directory (Use with dev mode).
--open-aea-dir PATH
: Path to open-aea repo (Use with dev mode).
--aev
: Deprecated. Applying environment variables when loading service config is now the default; this flag will be removed in v1.0.0.
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.
- 4d ago First seen · 361 lines · 0 tokens per session scan A ce72632efbe2
autonomy_deploy is a command published in the GitHub repository valory-xyz/open-autonomy (126 stars, last pushed 7d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 2,475 tokens. 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.
Other commands, from other repositories
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agentlas-local
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issue-amend
Re-snapshot the active issue's scope from the spec, clear verified and reviewed receipts, and record the change as a permanent amendment.
os-meeting
快速创建和管理AI团队会议.
spec-intake
Execute the canonical workflow: .agent/workflows/spec-intake.md.
q-research
Read the research-mode skill's SKILL.md for the full ruleset before proceeding. Follow all constraints, the source lookup cascade, the token budget, and the "what counts as cited" rules exactly.