SkillAgentSearch skills...

meta-search-builder

Medical literature search strategy generator. Given a user's natural-language description (e.g., meta-analysis topic, PICOS elements, research question), automatically extract medical entities (disease, intervention, population, outcomes) and generate professional search queries for seven major data…

Install / Use

npx skills add aipoch/medical-research-skills --skill meta-search-builder

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

92/100

Category

Automation

Supported Platforms

Universal

Our assessment of meta-search-builder

meta-search-builder scores 92/100 on our quality scale, 782nd of 2,464 Automation skills we index (top 32%).

Its SKILL.md is 6.4 KB long, well organised into 25 sections with 4 code examples: a thorough specification that gives an agent plenty to work with.

With 1,916 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
29/30
Structure
20/20
Description
15/15
Adoption
14/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 12 days ago, so meta-search-builder is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.

Automated pattern scan on 2026-09-30. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

meta-search-builder compared with similar skills

All 4 of these similar skills score higher than meta-search-builder; compare them before choosing.

SkillScoreStarsUpdatedFormat
meta-search-builder (this skill)by aipoch921.9k12d agoSKILL.md
Agent-Reachby Panniantong10086.2k14d agoCLAUDE.md
rufloby ruvnet10073.5ktodayCLAUDE.md
Scraplingby D4Vinci10084.6ktodayMCP Server
algorithmic-artby anthropics100177.9k7d agoSKILL.md

Frequently asked questions

How do I install meta-search-builder?
Run npx skills add aipoch/medical-research-skills --skill meta-search-builder. The install tabs above show the steps for each supported agent.
Which AI agents does meta-search-builder work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is meta-search-builder safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is meta-search-builder still maintained?
The repository was last updated 12 days ago, so meta-search-builder is actively maintained.

name: meta-search-builder description: Medical literature search strategy generator. Given a user's natural-language description (e.g., meta-analysis topic, PICOS elements, research question), automatically extract medical entities (disease, intervention, population, outcomes) and generate professional search queries for seven major databases (PubMed, Cochrane, Embase, Web of Science, CNKI, Wanfang, VIP). Useful for developing search strategies for systematic reviews and meta-analyses. license: MIT author: AIPOCH

Source: https://github.com/aipoch/medical-research-skills

Medical Literature Search Strategy Generator

When to Use

  • Use this skill when the request matches its documented task boundary.
  • Use it when the user can provide the required inputs and expects a structured deliverable.
  • Prefer this skill for repeatable, checklist-driven execution rather than open-ended brainstorming.

Key Features

  • Scope-focused workflow aligned to: Medical literature search strategy generator. Given a user's natural-language description (e.g., meta-analysis topic, PICOS elements, research question), automatically extract medical entities (disease, intervention, population, outcomes) and generate professional search queries for seven major databases (PubMed, Cochrane, Embase, Web of Science, CNKI, Wanfang, VIP). Useful for developing search strategies for systematic reviews and meta-analyses.
  • Documentation-first workflow with no packaged script requirement.
  • Reference material available in references/ for task-specific guidance.
  • Structured execution path designed to keep outputs consistent and reviewable.

Dependencies

  • Python: 3.10+. Repository baseline for current packaged skills.
  • Third-party packages: not explicitly version-pinned in this skill package. Add pinned versions if this skill needs stricter environment control.

Example Usage

Skill directory: 20260316/scientific-skills/Others/meta-search-builder
No packaged executable script was detected.
Use the documented workflow in SKILL.md together with the references/assets in this folder.

Example run plan:

  1. Read the skill instructions and collect the required inputs.
  2. Follow the documented workflow exactly.
  3. Use packaged references/assets from this folder when the task needs templates or rules.
  4. Return a structured result tied to the requested deliverable.

Implementation Details

See ## Workflow above for related details.

  • Execution model: validate the request, choose the packaged workflow, and produce a bounded deliverable.
  • Input controls: confirm the source files, scope limits, output format, and acceptance criteria before running any script.
  • Primary implementation surface: instruction-only workflow in SKILL.md.
  • Reference guidance: references/ contains supporting rules, prompts, or checklists.
  • Parameters to clarify first: input path, output path, scope filters, thresholds, and any domain-specific constraints.
  • Output discipline: keep results reproducible, identify assumptions explicitly, and avoid undocumented side effects.

Workflow

Step 1: Entity extraction

Extract PICOS elements from the user's input:

  1. P (Population): target population / disease
  2. I (Intervention): intervention
  3. C (Comparator): comparator (optional)
  4. O (Outcome): outcome measures (optional)
  5. S (Study): study type (default: RCT)

Extraction rules:

  • Limit the number of keywords to at most 5
  • Simplify descriptive phrases (e.g., "patients with ovarian cancer" -> "ovarian cancer")
  • Map non-standard terms to common medical terminology
  • Use standardized outcome terms where appropriate

Step 2: Generate search strategies for seven databases

See references/databases.md for database-specific syntax and examples.

Output format


## Extracted medical entities

- P (Population/Disease): xxx
- I (Intervention): xxx
- C (Comparator): xxx
- O (Outcome): xxx
- S (Study type): xxx

## Search strategies

### 1. PubMed
[search query]

### 2. Cochrane Library
[search query]

### 3. Embase
[search query]

### 4. Web of Science
[search query]

### 5. CNKI (China National Knowledge Infrastructure)
[search query]

### 6. Wanfang
[search query]

### 7. VIP
[search query]

When Not to Use

  • Do not use this skill when the required source data, identifiers, files, or credentials are missing.
  • Do not use this skill when the user asks for fabricated results, unsupported claims, or out-of-scope conclusions.
  • Do not use this skill when a simpler direct answer is more appropriate than the documented workflow.

Required Inputs

  • A clearly specified task goal aligned with the documented scope.
  • All required files, identifiers, parameters, or environment variables before execution.
  • Any domain constraints, formatting requirements, and expected output destination if applicable.

Output Contract

  • Return a structured deliverable that is directly usable without reformatting.
  • If a file is produced, prefer a deterministic output name such as meta_search_builder_result.md unless the skill documentation defines a better convention.
  • Include a short validation summary describing what was checked, what assumptions were made, and any remaining limitations.

Validation and Safety Rules

  • Validate required inputs before execution and stop early when mandatory fields or files are missing.
  • Do not fabricate measurements, references, findings, or conclusions that are not supported by the provided source material.
  • Emit a clear warning when credentials, privacy constraints, safety boundaries, or unsupported requests affect the result.
  • Keep the output safe, reproducible, and within the documented scope at all times.

Failure Handling

  • If validation fails, explain the exact missing field, file, or parameter and show the minimum fix required.
  • If an external dependency or script fails, surface the command path, likely cause, and the next recovery step.
  • If partial output is returned, label it clearly and identify which checks could not be completed.

Quick Validation

Run this minimal verification path before full execution when possible:

No local script validation step is required for this skill.

Expected output format:

Result file: meta_search_builder_result.md
Validation summary: PASS/FAIL with brief notes
Assumptions: explicit list if any

Related Skills

View on GitHub
GitHub Stars1.9k
CategoryAutomation
Updated12d ago
Forks175

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions