Analyze leaderboard score distributions, compression, selective reporting
Scanned 5/27/2026
Install via CLI
openskills install yogsoth-ai/de-anthropocentric-research-engine---
name: leaderboard-dynamics-analysis
description: Analyze leaderboard score distributions, compression, selective reporting
execution: subagent
prompt: ./prompt.md
input: leaderboard_data (model, score, date)
used-by: benchmark-archaeology
---
# Leaderboard Dynamics Analysis SOP
Analyze the dynamics of benchmark leaderboards: score distributions, compression over time, selective reporting patterns, and statistical artifacts.
## Input
- **leaderboard_data**: Structured data with (model_name, score, date, optional: model_size, paper_reference)
## Procedure
1. Compute score distribution statistics over time
2. Detect score compression (shrinking gap between top models)
3. Identify selective reporting patterns (cherry-picking, subset selection)
4. Analyze relationship between model size and score
5. Detect anomalies (withdrawn results, unreplicated claims)
## Output
Leaderboard health assessment with statistical evidence.
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Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 7 modes: full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review...