Skip to content
Back to skills

Detect Performance Discrepancy

ASecurity

Detect material score discrepancies for the same method/task across sources and propose likely explanatory condition differences.

  • 499 stars
  • 0 votes
  • 0 copies
  • 0 views
  • Added September 24, 2026
researchperformance

Security analysis

A100/100

Scanned September 24, 2026

npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill detect-performance-discrepancy --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Detect Performance Discrepancy?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Detect Performance Discrepancy
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/yogsoth-ai-detect-performance-discrepancy/badge)](https://www.skillsdirectory.com/skills/yogsoth-ai-detect-performance-discrepancy)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: detect-performance-discrepancy
description: "Detect material score discrepancies for the same method/task across sources and propose likely explanatory condition differences."
---

# detect-performance-discrepancy

## Purpose

Detect material score discrepancies for the same method or task across sources and identify plausible condition differences.

## Input contract

```yaml
required: [performance_records, method_key, task_key, metric_schema]
optional: [protocol_records, condition_schema, uncertainty_estimates]
constraints: [comparisons require aligned metric direction and declared conditions]
```

## Procedure

1. Align records by method, task, metric, and observation context.
2. Quantify score differences with uncertainty and identify materially different pairs.
3. Compare datasets, prompts, evaluators, budgets, and protocol conditions.
4. Rank plausible explanations and retain unresolved alternatives.

## Output contract

```yaml
produces: [discrepancy_pairs, condition_difference_map, explanation_candidates, residual_uncertainties]
delta_fields: [findings, evidence_updates, uncertainties, open_questions]
```

## Quality gates

- Materiality uses a declared comparison basis.
- Protocol mismatch is separated from method change.

## Failure and counterexamples

Do not call rounding noise a discrepancy or infer a method improvement from non-equivalent evaluation conditions.

## Provenance map

- `resolved: discrepancy-identification`
- `resolved: discrepancy-analysis`

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…