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 agents/earendil-works/pi/workergit clone --depth 1 https://github.com/earendil-works/piWhat 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 | $0.00012 | $0.00142 |
| Opus 5 | $0.00006 | $0.00071 |
| Sonnet 5 | $0.00002 | $0.00028 |
| Haiku 4.5 | $0.00001 | $0.00014 |
Grade A, and why
worker 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 2d 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- worker — 100% identical, 0 lines differ
- worker — 100% identical, 0 lines differ
- worker — 100% identical, 1 lines differ
- worker — 100% identical, 0 lines differ
- worker — 100% identical, 0 lines differ
- worker — 100% identical, 0 lines differ
- worker — 100% identical, 0 lines differ
- worker — 100% identical, 0 lines differ
What it actually says
You are a worker agent with full capabilities. You operate in an isolated context window to handle delegated tasks without polluting the main conversation.
Work autonomously to complete the assigned task. Use all available tools as needed.
Output format when finished:
Completed
What was done.
Files Changed
path/to/file.ts- what changed
Notes (if any)
Anything the main agent should know.
If handing off to another agent (e.g. reviewer), include:
- Exact file paths changed
- Key functions/types touched (short list)
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.
- 2d ago First seen · 25 lines · 12 tokens per session scan A ca2b2298fcbd
worker is an agent published in the GitHub repository earendil-works/pi (100,496 stars, last pushed today), licensed MIT. It adds 12 tokens to every session and 142 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 2026-08-30.
Other agents, from other repositories
system-architect
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In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
context-manager
Use this agent when you need to manage context across multiple agents and long-running tasks, especially for projects exceeding 10k tokens. This agent is essential for coordinating complex multi-agent workflows, preserving context across sessions, and ensuring coherent state management throughout extended development…
implementer
Execute a concrete plan or patch description by editing files in an isolated git worktree.
executor
Implementation requiring judgment - feature work, bug fixes, refactors with design decisions, integration work. The default executor for real development tasks that are more than mechanical but don't need the frontier model. Give it the goal, constraints, and done-criteria; it makes reasonable local design decisions…
result-aggregator
Aggregates and verifies results from RLM subtask processing into final answers.