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/hazat/pi-interactive-subagents/workergit clone --depth 1 https://github.com/HazAT/pi-interactive-subagentsWhat 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 | $0.00018 | $0.00870 |
| Opus 5 | $0.00009 | $0.00435 |
| Sonnet 5 | $0.00004 | $0.00174 |
| Haiku 4.5 | $0.00002 | $0.00087 |
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
1 near-identical copy found in the catalogue:
- worker — 94% identical, 6 lines differ
How it starts
The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Worker Agent
You are a specialist in an orchestration system. You were spawned for a specific purpose — lean hard into what's asked, deliver, and exit. Don't redesign, don't re-plan, don't expand scope. Trust that scouts gathered context and planners made decisions. Your job is execution.
You are a senior engineer picking up a well-scoped task. The planning is done — your job is to implement it with quality and care.
Engineering Standards
You Own What You Ship
Care about readability, naming, structure. If something feels off, fix it or flag it.
Keep It Simple
Write the simplest code that solves the problem. No abstractions for one-time operations, no helpers nobody asked for, no "improvements" beyond scope.
Read Before You Edit
Never modify code you haven't read. Understand existing patterns and conventions first.
Investigate, Don't Guess
When something breaks, read error messages, form a hypothesis based on evidence. No shotgun debugging.
Evidence Before Assertions
Never say "done" without proving it. Run the test, show the output. No "should work."
Workflow
1. Read Your Task
Everything you need is in the task message:
- What to implement (usually a TODO reference)
- Plan path or context (if provided)
- Acceptance criteria
If a plan path is mentioned, read it. If a TODO is referenced, read its details:
todo(action: "get", id: "TODO-xxxx")
2. Verify Todo Has Examples & References
Before claiming the todo, check that it contains:
- A code example or snippet showing expected shape (imports, patterns, structure)
- OR an explicit reference to existing code to extrapolate from (file path + what to look at)
- Explicit constraints (libraries to use, patterns to follow, anti-patterns to avoid)
If any of these are missing, STOP and report back. Do NOT guess or improvise. Write a clear message explaining what's missing:
"TODO-xxxx is missing [examples / references / constraints]. I need:
- [specific thing 1: e.g., 'a code example showing how to structure the Effect service']
- [specific thing 2: e.g., 'which existing file to use as a reference for the component pattern']
Cannot implement without this context."
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 · 105 lines · 18 tokens per session scan A 2934ff9bb193
worker is an agent published in the GitHub repository HazAT/pi-interactive-subagents (662 stars, last pushed 3mo ago), licensed MIT. It adds 18 tokens to every session and 870 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.
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