ma-scout

ma-scout is a skill for Claude Code from Aperivue/medsci-skills. It costs 41 tokens per session (6,998 once invoked), scanned A, original, MIT.

A topic-finding process for medical meta-analyses, which combine results from multiple studies. It starts either from a research topic or from a professor’s research profile, then assesses gaps, feasibility, and possible collaborators.

In plain words
What is it for?
Use it to generate and rank possible topics, examine a professor’s publication area, identify research gaps, and prepare a handoff to the meta-analysis workflow.
Why use it?
It helps narrow broad interests into research questions that are timely and realistically answerable. It also separates early topic selection from the later review and analysis work.

Skill for Claude Code

Written for Claude Code: ${CLAUDE_SKILL_DIR} variable. Also seen: model in frontmatter; reads .claude/ paths.

Part of the medsci-project plugin — 6 skills shipped together

Good fit Use it to generate and rank possible topics, examine a professor’s publication area, identify research gaps, and prepare a handoff to the meta-analysis workflow.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/aperivue/medsci-skills/ma-scout
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.

Any agent
npx skills add Aperivue/medsci-skills --skill ma-scout
Clone the repo
git clone --depth 1 https://github.com/Aperivue/medsci-skills

Made for: Claude Code.

Or install medsci-project, the plugin that ships this one along with the rest of its 6 skills.

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 ma-scout

README.md
[![agentmods](https://agentmods.dev/badge/skills/aperivue/medsci-skills/ma-scout/github.svg)](https://agentmods.dev/skills/aperivue/medsci-skills/ma-scout)
Your own site
<a href="https://agentmods.dev/skills/aperivue/medsci-skills/ma-scout"><img src="https://agentmods.dev/badge/skills/aperivue/medsci-skills/ma-scout/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 ma-scout

Your own site · 80×15
<a href="https://agentmods.dev/skills/aperivue/medsci-skills/ma-scout"><img src="https://agentmods.dev/badge/skills/aperivue/medsci-skills/ma-scout.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,998 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. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 4 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Excessive Agency · line 6
    Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.
    Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
  • medium Agent Snooping · line 122
    Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.
    Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
  • medium Rogue Agent · line 263
    Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.
    Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
  • medium Excessive Agency · line 382
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
How audits are shown
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 $0.00041 $0.06998
Opus 5 $0.00020 $0.03499
Sonnet 5 $0.00008 $0.01400
Haiku 4.5 $0.00004 $0.00700

Measured 11d ago against content hash 3ebbd36111d7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

ma-scout 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 11d 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.

skills/ma-scout/SKILL.md · 641 lines

How it starts

The opening of the file, as written. The whole thing — 641 lines — stays where its author put it; the contents beside it link to each section on GitHub.

MA Scout Skill

You are helping a medical researcher discover meta-analysis topics. Two modes are available depending on the starting point.

This skill handles the pre-protocol phase — from idea to ranked topic list. For actual MA execution (PROSPERO, screening, analysis), hand off to /meta-analysis.

Mode Selection

Determine the mode from user input:

Signal Mode
Professor name or profile URL provided A: Professor-first
Clinical question, keyword, trend, or "find me a topic" B: Topic-first
Both supplied (e.g., "this topic with this professor") A (topic as filter)

If ambiguous, ask the user whether to search by professor (supervisor-first) or by topic (question-first).

Communication Rules

  • Communicate with the user in their preferred language (typically Korean).
  • Research questions, PICO/PIRD, and README content in English.
  • Medical terminology always in English.

Inputs

Mode A: Professor-first

  • Professor name (native-language + English)
  • Profile URL (ScholarWorks, SKKU Faculty, Google Scholar, ORCID)
  • PubMed author link (preferably with cauthor_id for disambiguation)
  • Known specialty (e.g., "thoracic imaging", "abdominal imaging")
  • Affiliation history (e.g., "Hospital A → Hospital B → retired")
  • Minimum required: name + at least one profile URL or PubMed link

Mode B: Topic-first

  • Clinical question or keyword (e.g., "AI for lung-nodule malignancy prediction", "dual-energy CT body composition")
  • Radiology subspecialty scope (e.g., thoracic, abdominal, neuro)
  • MA type preference (DTA, prognostic, intervention — optional)
  • Desired role: solo first author / co-first / supervisor-matched
  • Minimum required: clinical question or keyword

Workflow

Mode A (Professor-first): Phase 0 → 1 → 2 → 3 → 4 → 5 Mode B (Topic-first): T-Phase 0 → T-1 → T-2 → T-3 → T-4 → T-5 Phase 2 (MA Gap Analysis) and Phase 4 (README template) are shared between both modes.

Read the full file on GitHub · 641 lines

Files

What ships with it

3 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.

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. 11d ago First seen · 641 lines · 41 tokens per session scan A 3ebbd36111d7

Subscribe to this mod's changes

ma-scout is a skill published in the GitHub repository Aperivue/medsci-skills (292 stars, last pushed 4d ago), licensed MIT. It adds 41 tokens to every session and 6,998 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.

Related

Other skills, from other repositories

clinical-trials-search

Search ClinicalTrials.gov with natural language queries. Find clinical trials, enrollment, and outcomes using Valyu semantic search.

beita6969/ScienceClaw · 28 tokens

shidi

A Chinese-language research assistant role that turns a user’s ideas into literature reviews, experiment plans, figures and organised data.

IcyCreamDAS/shidi-skill · 126 tokens

clinical-research

Use when designing a prospective clinical study before submission — selecting and classifying endpoints (primary / key-secondary / exploratory, with surrogate-endpoint flagging), estimating sample size and power for two-arm designs (means / proportions / survival), or scoring a study plan for feasibility and a GO /…

bestagentkits/agency-skills · 152 tokens

sr-search-record

An automated literature-review search and screening workflow using OpenAlex, an open database and API for scholarly research, and Zotero, a reference manager.

qiaomiaojoe/ai-academic-workflow · 350 tokens

review-synthesis

A literature-review workflow that combines evidence from the full text of selected research papers into a findings document. It uses different review methods for systematic, semi-systematic, and integrative reviews.

qiaomiaojoe/ai-academic-workflow · 285 tokens

review-draft

A workflow for expanding a first draft of a review article into a structured academic manuscript. A review article combines and organizes existing research rather than reporting a new experiment.

qiaomiaojoe/ai-academic-workflow · 281 tokens