DeepScientist Worker Base

DeepScientist Worker Base is an agent for Claude Code from ResearAI/DeepScientist. It costs 16 tokens per session (329 once invoked), scanned A, original, Apache-2.0.

A shared work contract for DeepScientist workers, which are specialized agents carrying out parts of a research project.

In plain words
What is it for?
Use it to define worker scope, isolate work in a project branch or folder, record commands and results, and create progress or handoff reports.
Why use it?
It keeps each worker within its assigned area and leaves evidence that the lead agent can review, including when work fails or is blocked.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md).

Good fit Use it to define worker scope, isolate work in a project branch or folder, record commands and results, and create progress or handoff reports.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/researai/deepscientist/worker-base
About the project

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.

ResearAI/DeepScientist · 3,376 stars · on GitHub

Install

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.

Clone the repo
git clone --depth 1 https://github.com/ResearAI/DeepScientist

Made for: Claude Code.

Wrote 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.

agentmods badge for DeepScientist Worker Base

README.md
[![agentmods](https://agentmods.dev/badge/agents/researai/deepscientist/worker-base/github.svg)](https://agentmods.dev/agents/researai/deepscientist/worker-base)
Your own site
<a href="https://agentmods.dev/agents/researai/deepscientist/worker-base"><img src="https://agentmods.dev/badge/agents/researai/deepscientist/worker-base/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.

agentmods 80×15 button for DeepScientist Worker Base

Your own site · 80×15
<a href="https://agentmods.dev/agents/researai/deepscientist/worker-base"><img src="https://agentmods.dev/badge/agents/researai/deepscientist/worker-base.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 16 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 329 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00016 $0.00329
Opus 5.5 $0.00006 $0.00132
Sonnet 5.5 $0.00003 $0.00066
Haiku 4.5 $0.00002 $0.00033

Measured 1mo ago against content hash 66db95095dd8, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

DeepScientist Worker Base 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.

assets/text/agents/worker-base.md · 45 lines

What it actually says

Worker Execution Contract

You are a specialized worker operating under a quest-level lead plan.

Scope

  • Focus on the assigned task, branch, worktree, and evidence contract.
  • Prefer finishing one clear unit of work over partially touching many unrelated things.

Isolation rules

  • Work only inside the assigned quest_root and, when provided, the assigned worktree_root.
  • Do not merge or promote your own branch-level work into the quest branch without an explicit lead decision.
  • Do not create hidden shared state outside documented files, memory, or artifact.

Required durable outputs

Each meaningful worker pass should leave behind:

  • progress or milestone artifacts for long-running work
  • a run/report/handoff artifact for the result
  • optional memory cards only when the lesson is reusable beyond the immediate task

Evidence rules

  • Record commands, configs, diffs, logs, metrics, and report paths so a lead can audit the result later.
  • Report failures honestly; a failed run still needs a durable summary and blocker description.

Escalation rules

  • If the task contract is missing a critical dependency, record a blocked result instead of guessing.
  • If you need a different branch, worktree, or baseline attachment, stop and surface the gap clearly.

Hand-off rules

  • Summarize what changed.
  • Point to the exact output paths.
  • State whether the lead should continue, rerun, merge, branch, or stop.
Changes

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.

  1. 1mo ago First seen · 45 lines · 16 tokens per session scan A 66db95095dd8

Subscribe to this mod's changes

DeepScientist Worker Base is an agent published in the GitHub repository ResearAI/DeepScientist (3,376 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 16 tokens to every session and 329 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.

Related

Other agents, from other repositories

editor

Journal editor who desk-reviews manuscripts, selects two referees with deliberately different dispositions, calibrates to a target journal from .claude/references/journal-profiles.md, and synthesizes an editorial decision (FATAL / ADDRESSABLE / TASTE). Used by /review-paper --peer [journal].

pedrohcgs/claude-code-my-workflow · 64 tokens

Geoprocessing Specialist

ArcPy and Python toolbox expert who automates spatial workflows — builds .pyt toolboxes, Model Builder processes, batch geoprocessing automation, and custom analysis scripts for ArcGIS Pro.

SHAdd0WTAka/Zen-Ai-Pentest · 45 tokens

research-scout

Scans the NeqSim codebase to discover scientific paper opportunities that will drive code improvement. Every paper must improve NeqSim — adding tests, validating models against data, hardening algorithms, or implementing new capabilities. Produces ranked, actionable topics that feed into the planner agent.

equinor/neqsim · 61 tokens

astronomical-instrumentation-scientist

Reasons from system-level error budgets, the diffraction limit and Strehl ratio, detector figures of merit, and resolving power through Zemax/Code V tolerancing, ETC radiometry, AO modeling, and on-sky standard-star commissioning while treating flexure drift, IR persistence, ghosts, and quasi-static speckles as…

K-Dense-AI/scientific-agents · 78 tokens

mathodology-problem-analyst

Understand contest questions, requirements, mechanisms and decision needs.

sweetcornna/mathodology · 20 tokens

epidemiology-research-agent

Research agent for epidemiology and public health.

benbrastmckie/nvim · 8 tokens