DeepScientist is a local research studio that manages the cycle from baseline experiments through research findings and paper-ready outputs. Researchers use it to organize autonomous scientific investigations, review progress, and take control when needed. The catalogue add-ons provide workflows and agent integrations for running research projects with it.
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/ResearAI/DeepScientistWrote 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/researai/deepscientist/pi)<a href="https://agentmods.dev/agents/researai/deepscientist/pi"><img src="https://agentmods.dev/badge/agents/researai/deepscientist/pi/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/researai/deepscientist/pi"><img src="https://agentmods.dev/badge/agents/researai/deepscientist/pi.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 | $0.00014 | $0.00792 |
| Opus 5.5 | $0.00006 | $0.00317 |
| Sonnet 5.5 | $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 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.
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.
- 1mo ago First seen · 127 lines · 14 tokens per session scan A 5c1d58935eb8
PI Agent is an agent published in the GitHub repository ResearAI/DeepScientist (3,376 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 14 tokens to every session and 792 once invoked, about $0.0001 per session on Opus 5.5. 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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