Agent Skills

Meta Title Generator

AIPOCH

Generates Meta-Analysis research titles based on user keywords, utilizing PubMed search results if available, or creative generation otherwise. Use when the user wants to brainstorm or generate titles for a meta-analysis, specifically starting from keywords or a topic.

3
0
FILES
meta-title-generator/
skill.md
scripts
search_pubmed.py
references
title_generation_prompts.md
85100Total Score
View Evaluation Report
Core Capability
77 / 100
Functional Suitability
9 / 12
Reliability
9 / 12
Performance & Context
8 / 8
Agent Usability
12 / 16
Human Usability
7 / 8
Security
8 / 12
Maintainability
9 / 12
Agent-Specific
15 / 20
Medical Task
20 / 20 Passed
95Generates Meta-Analysis research titles based on user keywords, utilizing PubMed search results if available, or creative generation otherwise
4/4
91Generates Meta-Analysis research titles based on user keywords, utilizing PubMed search results if available, or creative generation otherwise
4/4
89Generates Meta-Analysis research titles based on user keywords, utilizing PubMed search results if available, or creative generation otherwise
4/4
89Packaged executable path(s): scripts/search_pubmed.py
4/4
89End-to-end case for Scope-focused workflow aligned to: Generates Meta-Analysis research titles based on user keywords, utilizing PubMed search results if available, or creative generation otherwise. Use when the user wants to brainstorm or generate titles for a meta-analysis, specifically starting from keywords or a topic
4/4

SKILL.md

Meta-Analysis Title Generator

When to Use

  • Use this skill when you need generates meta-analysis research titles based on user keywords, utilizing pubmed search results if available, or creative generation otherwise. use when the user wants to brainstorm or generate titles for a meta-analysis, specifically starting from keywords or a topic in a reproducible workflow.
  • Use this skill when a data analytics task needs a packaged method instead of ad-hoc freeform output.
  • Use this skill when the user expects a concrete deliverable, validation step, or file-based result.
  • Use this skill when scripts/search_pubmed.py is the most direct path to complete the request.
  • Use this skill when you need the meta-title-generator package behavior rather than a generic answer.

Key Features

  • Scope-focused workflow aligned to: Generates Meta-Analysis research titles based on user keywords, utilizing PubMed search results if available, or creative generation otherwise. Use when the user wants to brainstorm or generate titles for a meta-analysis, specifically starting from keywords or a topic.
  • Packaged executable path(s): scripts/search_pubmed.py.
  • 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

See ## Usage above for related details.

cd "20260316/scientific-skills/Data Analytics/meta-title-generator"
python -m py_compile scripts/search_pubmed.py
python scripts/search_pubmed.py --help

Example run plan:

  1. Confirm the user input, output path, and any required config values.
  2. Edit the in-file CONFIG block or documented parameters if the script uses fixed settings.
  3. Run python scripts/search_pubmed.py with the validated inputs.
  4. Review the generated output and return the final artifact with any assumptions called out.

Implementation 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: scripts/search_pubmed.py.
  • 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.

Description

This skill generates research titles for Meta-Analysis studies. It takes user-provided keywords, searches PubMed to find relevant literature, and proposes titles based on the findings. If no literature is found, it creatively generates titles based on the keywords. It outputs 5 titles in both English and Chinese.

Usage

1. Search and Generate

When the user provides keywords (e.g., "lung cancer", "hypertension"), follow these steps:

  1. Generate Search Strategy: Convert the user's keywords into a PubMed search strategy string (English keywords combined with AND/OR).
  2. Search PubMed: Run scripts/search_pubmed.py with the search strategy.
    • This script returns a JSON object containing the count of results and a summary of papers (if any).
  3. Check Results:
    • If the result count is > 0:
      • Analyze the papers found (provided in the script output).
      • Generate 5 Meta-Analysis titles based on the PICOs (Participant, Intervention, Comparison, Outcome, Study design) of these papers.
    • If the result count is 0:
      • Generate 5 Meta-Analysis titles creatively based on the original keywords.
  4. Format Output:
    • Present the titles in a specific JSON format containing "Title1" to "Title5", each with "English" and "Chinese" fields.
    • Ensure titles are strictly for Meta-Analysis (not clinical trials).
    • Ensure interventions specify a drug or treatment method.

Quality Rules

  • Meta-Analysis Focus: Titles must clearly indicate a Systematic Review and Meta-Analysis.
  • Specific Interventions: Do not use broad terms; specify the drug or method.
  • Bilingual Output: Every title must have an English and Chinese version.

Reference Material

For detailed prompting strategies used in title generation, see references/title_generation_prompts.md.