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/hoja-solutions/agent-stdlib/autonomous-loopgit clone --depth 1 https://github.com/Hoja-Solutions/agent-stdlibWhat 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 | $0.00020 | $0.00468 |
| Opus 5 | $0.00010 | $0.00234 |
| Sonnet 5 | $0.00004 | $0.00094 |
| Haiku 4.5 | $0.00002 | $0.00047 |
Grade A, and why
autonomous-loop 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 yesterday.
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
Help the user run the parallel-autonomous-agents pattern from this pack. Follow
the parallel-autonomous-agents skill.
Context for what they passed: $ARGUMENTS
The loop itself runs in the shell, not inside this session, because it spawns many fresh headless agent sessions over time. Your job here is to set it up and explain it, not to run an overnight loop yourself.
Do this:
-
Build the task list. If they gave a tasks file, use it. Otherwise turn their goal into a
tasks.txtwith one independent, self-contained task per line. Tasks that touch the same files should be separate lines so agents do not collide on them. -
Explain the coordination. The lock registry (
scripts/locks.py) is how agents avoid duplicating work: claiming a task atomically creates a lock file, and only one agent can win the race. Stale locks (from a crashed agent) get reaped after a threshold. -
Show how to launch. Each agent is one copy of the loop runner:
scripts/autonomy_loop.sh tasks.txt agent-1Run several copies in parallel (separate terminals or containers), each with a distinct agent id. They share
current_tasks/and stay off each other's work. The loop callsclaude -pby default; for another harness setAGENT_RUNNER, e.g.AGENT_RUNNER="opencode run" scripts/autonomy_loop.sh tasks.txt agent-1. -
Point at the steering mechanism. With no human in the loop, the test suite is the steering wheel. Confirm they have a comprehensive suite and that its output is machine-readable (single-line
ERROR: <reason>results an agent can grep), per the skill.
Do not start a long-running loop from this session. Hand the user the commands and let them run it where they can watch it.
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.
- yesterday First seen · 45 lines · 20 tokens per session scan A e683b1fc0290
autonomous-loop is a command published in the GitHub repository Hoja-Solutions/agent-stdlib (1 stars, last pushed 1mo ago), licensed MIT. It adds 20 tokens to every session and 468 once invoked, about $0.0001 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.
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