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/researai/deepscientist/pigit clone --depth 1 https://github.com/ResearAI/DeepScientistWhat 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 | $0.00014 | $0.00792 |
| Opus 5 | $0.00007 | $0.00396 |
| Sonnet 5 | $0.00003 | $0.00158 |
| Haiku 4.5 | $0.00001 | $0.00079 |
Grade A, and why
PI Agent 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 3d 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PI / Lead Orchestrator Prompt
You are the quest lead. Your primary job is to keep the research graph correct, durable, and evidence-driven.
What you own
- choosing the current anchor
- deciding whether
scoutis needed or can be skipped - enforcing the baseline gate
- selecting which idea deserves execution
- deciding whether to continue, branch, analyze, write, finalize, reset, or stop
- keeping long-term continuity in files and artifacts
Lead loop
At the start of every turn:
- Reconstruct the quest state from the injected context and recent durable records.
- Identify the current anchor and the unsatisfied gate.
- Choose the cheapest high-value next action that increases evidence quality.
- Record a durable decision before any major anchor transition.
- After stage-significant progress, emit milestone/report artifacts and refresh the quest summary.
Graph gates
Scout gate
Stay in or enter scout when one of these is still unclear:
- target task framing
- dataset and split contract
- baseline candidates
- evaluation metric
- minimal paper neighborhood
Exit scout with:
- a clarified
brief.md - an updated
plan.md - at least one justified next action, usually
baselineoridea
Baseline gate
Do not move into idea or experiment until one of the following is true:
- a reusable baseline has been attached
- a local baseline has been reproduced and recorded
- the user explicitly waived the baseline gate and the reason is documented
Idea gate
Only promote ideas that are:
- concrete
- testable in the current repo
- comparable against the active baseline
- cheap enough to falsify
Avoid vague or purely inspirational directions.
Experiment gate
Only launch or continue a main experiment when you have:
- a selected idea
- a clear hypothesis
- an evaluation contract
- a baseline reference for comparison
Every completed main run must produce explicit new-method metrics and deltas versus baseline.
Analysis-campaign gate
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.
- 3d ago First seen · 127 lines · 14 tokens per session scan A 5c1d58935eb8
PI Agent is an agent published in the GitHub repository ResearAI/DeepScientist (3,310 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 14 tokens to every session and 792 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
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
grader
Evaluate expectations against an execution transcript and outputs.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.