--- name: meta-feasibility-analyzer-e90fc04c9eba description: Analyzes the feasibility of a proposed Meta-analysis topic by searching for existing Meta-analyses and Clinical Trials on PubMed/ClinicalTrials.gov. Use when you need to evaluate if a topic is viable for a new Meta-analysis. license: MIT author: AIPOCH --- > **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills) # Meta Feasibility Analyzer This skill evaluates the feasibility of conducting a new Meta-analysis on a given topic (title). It checks for existing Meta-analyses and available Clinical Trials to determine if there is a gap or sufficient new evidence. ## When to Use - Use this skill when you need analyzes the feasibility of a proposed meta-analysis topic by searching for existing meta-analyses and clinical trials on pubmed/clinicaltrials.gov. use when you need to evaluate if a topic is viable for a new meta-analysis 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/feasibility_ops.py` is the most direct path to complete the request. - Use this skill when you need the `meta-feasibility-analyzer` package behavior rather than a generic answer. ## Key Features - Scope-focused workflow aligned to: Analyzes the feasibility of a proposed Meta-analysis topic by searching for existing Meta-analyses and Clinical Trials on PubMed/ClinicalTrials.gov. Use when you need to evaluate if a topic is viable for a new Meta-analysis. - Packaged executable path(s): `scripts/feasibility_ops.py`. - 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 ```bash cd "20260316/scientific-skills/Data Analytics/meta-feasibility-analyzer" python -m py_compile scripts/feasibility_ops.py python scripts/feasibility_ops.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/feasibility_ops.py` with the validated inputs. 4. Review the generated output and return the final artifact with any assumptions called out. ## 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: `scripts/feasibility_ops.py`. - 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 Follow these steps to perform the analysis. ### 1. Generate Search Query First, analyze the user's proposed title to generate a valid PubMed search query. **Prompt for LLM:** ```text Role: Medical Search Expert Task: Extract keywords from the following title and create a PubMed search query. Title: "{{input_the_title}}" Rules: 1. Extract keywords (Disease, Intervention, Outcome). 2. Convert to standard MeSH terms if possible. 3. Combine with AND/OR. 4. Enclose the final query in braces {}. 5. Do NOT include "meta analysis" in the query. Example Output: {(ovarian cancer) AND (chemotherapy) AND (bevacizumab)} ``` ### 2. Extract Query String Run the extraction script to get the clean query string. ```bash python scripts/feasibility_ops.py extract --text "{{llm_output}}" ``` Store the output as `{{search_query}}`. ### 3. Search Clinical Trials Search for Clinical Trials via the PubMed API. ```bash python scripts/feasibility_ops.py search --query "{{search_query}}" --type clinical ``` Store the result JSON as `{{clinical_json}}`. ### 4. Process Clinical Results Format the clinical trial results and check the count. ```bash python scripts/feasibility_ops.py clinical --json '{{clinical_json}}' --query "{{search_query}}" ``` Parse the output JSON to get: - `clinical_count`: Number of trials found. - `clinical_summary`: Formatted summary string. ### 5. Feasibility Check (Stage 1) **If `clinical_count` == 0:** - The topic is **NOT FEASIBLE** due to lack of primary studies. - Output: "⚠️ Sorry, no relevant clinical studies found for this title. This topic is likely not feasible." - **STOP**. **If `clinical_count` > 0:** - Proceed to Step 6. ### 6. Search Meta-Analyses Search for existing Meta-analyses via the PubMed API using the same query. ```bash python scripts/feasibility_ops.py search --query "{{search_query}}" --type meta ``` Store the result JSON as `{{meta_json}}`. ### 7. Process Meta Results Format the meta-analysis results. ```bash python scripts/feasibility_ops.py meta --json '{{meta_json}}' ``` Parse the output JSON to get: - `meta_summary`: Formatted summary string. ### 8. Final Feasibility Analysis Analyze the results to determine final feasibility. **Prompt for LLM:** ```text Role: Clinical Research Expert Task: Assess Meta-analysis feasibility. Input: Title: "{{input_the_title}}" Existing Meta-Analyses: {{meta_summary}} Existing Clinical Trials: {{clinical_summary}} Logic: 1. If NO existing Meta-analyses + YES Clinical Trials -> ✅ FEASIBLE. 2. If YES existing Meta-analyses: - Check the dates. Are there new Clinical Trials published AFTER the latest Meta-analysis? - If YES new trials -> ✅ FEASIBLE (Update is possible). - If NO new trials -> ⚠️ NOT FEASIBLE (Already covered). Output Format: "{{input_the_title}}" [Conclusion: ✅ Feasible / ⚠️ Not Feasible] Reason: [Explain based on the logic above] ``` ### 9. Output Present the final analysis to the user. --- Source attribution: aipoch Original project: https://github.com/aipoch/medical-research-skills/blob/686e09dfdb45d9fa1a08664f06bb93769b3c9d91/scientific-skills/Data%20Analysis/meta-feasibility-analyzer/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Copyright (c) 2026 AIpoch Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: aipoch Original project: https://github.com/aipoch/medical-research-skills/blob/686e09dfdb45d9fa1a08664f06bb93769b3c9d91/scientific-skills/Data%20Analysis/meta-feasibility-analyzer/SKILL.md Attribution basis: Source repository record Fields of work: Data & Analytics, Education & Research, Healthcare & Life Sciences Roles: Clinical Research, Data Analyst, Researcher Specialties: API Tools: Pubmed, Clinicaltrials.Gov Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: ea9eba7d3be0d70ba81b906b92fb0d55a0659908f8e36385dfcb2647d4683cb5