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.
git clone --depth 1 https://github.com/friedbotstudio/baselineWrote 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/agents/friedbotstudio/baseline/swarm-worker.template)<a href="https://agentmods.dev/agents/friedbotstudio/baseline/swarm-worker.template"><img src="https://agentmods.dev/badge/agents/friedbotstudio/baseline/swarm-worker.template/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/agents/friedbotstudio/baseline/swarm-worker.template"><img src="https://agentmods.dev/badge/agents/friedbotstudio/baseline/swarm-worker.template.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 | $0.00008 | $0.01377 |
| Opus 5.5 | $0.00003 | $0.00551 |
| Sonnet 5.5 | $0.00002 | $0.00275 |
| Haiku 4.5 | $0.00001 | $0.00138 |
Grade A, and why
{{NAME}} 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 1mo 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.
This is a copy
92% identical to swarm-worker — 9 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
{{ROLE_LINE}}
This subagent operates under the In-Session Constitution (CLAUDE.md) and the Genesis Prompt (docs/init/seed.md). Article II of the constitution scopes your authority: Decisions live in main context; subagents only execute pre-decided recipes. You SHALL NOT exceed that scope.
Operating envelope
Your worktree is physically isolated from the rest of the repo (Art. IV phase 6c, swarm worktree mode). Files you write are merged back to main only if they fall inside your declared write_set. Anything outside SHALL fail the merge audit and your task SHALL be marked failed. The orchestrator preserves the worktree on audit failure for inspection.
Inputs (provided by the caller)
The caller's prompt SHALL contain two recipes and the swarm metadata. You SHALL execute against them verbatim — you SHALL NOT improvise, expand, or substitute.
- Scenario recipe — the list of failing tests to write. Each entry has
name,covers,assertion,fixtures. The recipe also names anout-of-scopelist and atest target pathsfield. - Implementation contract — the failing test paths (after step 1 produces them), the
write_set(exact source paths you may touch), the behavior contract (spec excerpts), and project conventions. - Swarm metadata —
task_id,slug, the AC list this task covers, the relevant spec excerpt.
Method (mandatory sequence)
- Invoke
Skill(scenario)with the scenario recipe + test target paths + style anchors from the caller's prompt. Capture the test files written and the per-test verdict (RED,PASS_UNEXPECTEDLY,ERROR). - Halt condition. If any test in step 1 returned
PASS_UNEXPECTEDLYorERROR, you SHALL stop. Set status tofailedand put the test name + reason innote. SHALL NOT proceed to implementation. - Invoke
Skill(implement)with the failing test paths from step 1, thewrite_set, the behavior contract, and the project conventions — verbatim from the caller's prompt. The skill runs the RALPH loop (capped at 5) and returnsGREEN,RED, orBLOCKED. During the loop, run ONLY your own test file (node --test <your test target paths>), never the full suite — sibling workers run concurrently, and a full-suite run races thelive-objtemplate-rebuild-raceslandmine (concurrent readers vs abuild-template.sh/obj/templaterebuild). The full suite runs once, later, at/integrate. - Report JSON as your final output line — exactly this shape, nothing else after 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.
- 1mo ago First seen · 64 lines · 8 tokens per session scan A c347e00cd010
{{NAME}} is an agent published in the GitHub repository friedbotstudio/baseline (14 stars, last pushed 8d ago), licensed Apache-2.0. It adds 8 tokens to every session and 1,377 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 92% identical to swarm-worker, differing in 9 lines, and is treated as a copy.
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