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.
npx agentmods add skills/researai/deepscientist/decisionnpx skills add ResearAI/DeepScientist --skill decisiongit 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/skills/researai/deepscientist/decision)<a href="https://agentmods.dev/skills/researai/deepscientist/decision"><img src="https://agentmods.dev/badge/skills/researai/deepscientist/decision.svg" alt="Measured on agentmods" 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 | $0.00035 | $0.02184 |
| Opus 5 | $0.00017 | $0.01092 |
| Sonnet 5 | $0.00007 | $0.00437 |
| Haiku 4.5 | $0.00003 | $0.00218 |
Grade A, and why
decision 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 5d 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 — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Decision
Use this skill whenever continuation is non-trivial. Use it to make one route judgment from durable evidence and then get the quest moving again.
Match signals
Use decision when:
- the next stage is not obvious
- the evidence is mixed
- the current line may need to stop
- the quest needs a branch, reset, or reuse-baseline judgment
- a user preference-sensitive choice remains
- a blocker needs an explicit route
Do not use decision when:
- the active mainline is still too ambiguous for a real route judgment and should first be reconciled through
intake-audit - the next move is already obvious from durable evidence and can proceed directly
- the task is really baseline recovery, scouting, ideation, or execution rather than a route judgment
One-sentence summary
Make one route judgment from durable evidence, record the verdict and smallest valid action, then keep the quest moving.
Control workflow
- Check whether the board is decision-ready.
If the current mainline, latest decisive result, or stale-route state is unclear, route through
intake-auditfirst. - State the real question and gather only decision-relevant evidence. Compress the strongest support, strongest contradiction, main risk, main cost, and what is genuinely new.
- Choose the smallest canonical action that resolves the current state. Make the winner, main rejected alternatives, and the decisive reason explicit.
- Record the decision durably. Include verdict, action, reason, evidence paths, and next stage or next direction.
- Ask the user only when local evidence cannot safely resolve a real preference, scope, or cost choice.
AVOID / pitfalls
- Do not repeat the same decision without new evidence.
- Do not decide from vibe, momentum, or optimism.
- Do not hide a blocked state behind a vague “continue”.
- Do not launch analysis campaigns casually when the expected information gain is weak.
- Do not choose among candidate packages without naming why the alternatives lost.
- Do not imply baseline reuse is resolved unless the concrete attachment and confirmation path is clear.
- Do not choose
finalizefor a paper line unless manuscript coverage reportssubmission_ready=true; a draft checkpoint routes back towrite, and a review package routes toreview. - Do not keep a paper route alive after a publishability stop-loss finding. If durable evidence shows that novelty, evidence sufficiency, or reader value has collapsed beyond reasonable narrowing, recommend
stoporbranch, and record any narrowed non-paper objective as the next direction rather than as a new action. Do not executestopfor a low-quality paper judgment without asking the user to confirm that route.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago First seen · 202 lines · 35 tokens per session scan A 95d3431099a4
decision is a skill published in the GitHub repository ResearAI/DeepScientist (3,314 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 35 tokens to every session and 2,184 once invoked, about $0.0002 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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