Cluster weaknesses from evaluated papers and generate gap reports.
npx skills add https://github.com/ZhangHanbo/alpha_research --skill gap-analysis-zhanghanbo
Please help me install this Agent Skill. Skill: gap-analysis Source: https://github.com/ZhangHanbo/alpha_research/tree/main/skills/gap-analysis Command: npx skills add https://github.com/ZhangHanbo/alpha_research --skill gap-analysis-zhanghanbo
Researchers need to uncover systemic weaknesses across many evaluated papers to define open problems, but manually reviewing each paper is time‑consuming and error‑prone.
Use case: After running a literature‑survey that produces 50 evaluation records, invoke this skill to automatically generate a structured gap report that powers the next significance‑screening step.
Ask the gap-analysis skill to synthesize research gaps from the latest literature survey.
High-intent search queries and answers about installing and using this skill.
To identify research gaps from a literature survey, you can aggregate evaluation records, apply semantic clustering to group recurring weaknesses, and verify candidate gaps using search APIs. This process synthesizes concrete research directions and flags items for human judgment.
The best way to cluster recurring limitations across evaluated papers is using semantic clustering on aggregated weakness data. This method groups identified weaknesses into meaningful gap categories and highlights systemic problems found within your literature survey outputs.
Yes, you need Python execution to generate a gap analysis report from JSONL records. The system requires Python for data aggregation, relies on project memory JSONL records for input, and uses search APIs for automated verification of candidate gaps.
Semantic clustering verifies real research gaps by cross-referencing clustered weaknesses against your Hamming list and validating them via search APIs. This automated verification ensures proposed research directions are backed by motivating papers and existing literature.
Yes, you can use Bash, Grep, Read, and Write to aggregate weakness counts for a robotics literature review. The process avoids external tools beyond these, relying on Python execution to parse JSONL records and summarize paper details efficiently.
You should not use automated gap synthesis if your project lacks JSONL records or Python execution capabilities. The system depends on structured evaluation data from a prior literature survey and requires search APIs to verify candidate gaps and generate persisted reports.
bettercallfanSearch JSONL trajectory records by coordinates, distance, and duration.
prathamchopra001Synthesize research findings into structured conclusions with confidence scores.
BarnemaxCross-reference species suggestions against existing fixtures and rank candidates by relationship density.
kangning-huangSimulate adversarial peer review to identify methodological and statistical weaknesses in research documents.
