Skip to content
Back to skills

Specify Metrics

ASecurity

Define primary/secondary metrics, estimands, directionality, uncertainty reporting, and decision thresholds before analysis.

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

Security analysis

A100/100

Scanned September 24, 2026

npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill specify-metrics --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Specify Metrics?

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

Security grade badge for Specify Metrics
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/yogsoth-ai-specify-metrics/badge)](https://www.skillsdirectory.com/skills/yogsoth-ai-specify-metrics)

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: specify-metrics
description: "Define primary/secondary metrics, estimands, directionality, uncertainty reporting, and decision thresholds before analysis."
---

# specify-metrics

## Purpose

Define primary/secondary metrics, estimands, directionality, uncertainty reporting, and decision thresholds before analysis.

## Input contract

```yaml
required: [estimand, outcome_schema, decision_thresholds]
optional: [evidence, assumptions, prior_results]
constraints: [use named scientific objects; retain provenance and missingness; $\alpha$ = 0.05 and power = 0.8 where applicable]
```

## Procedure

1. Validate the typed inputs and state the decision this operation must support.
2. Apply the declared operation to the named object; record intermediate values that affect interpretation.
3. Check boundary conditions and counterexamples, then emit the result with uncertainty and source links.

If estimands, metrics, and decision thresholds are fixed, consider `estimate-sample-size` as the next tactic.

## Output contract

```yaml
produces: [specify_metrics_result, evidence_trace, uncertainties]
delta_fields: [evidence_updates, uncertainties]
```

## Quality gates

- Inputs are named scientific objects with compatible schemas.
- Every material result has a derivation or source reference.
- Fixed statistical criteria remain exact where applicable: $\alpha$ 0.05 and power 0.8.

## Failure and counterexamples

Return a failed operation with the violated precondition when inputs are incomplete, assumptions are unsupported, or a counterexample defeats the result.

## Provenance map

- intermediate: experiment-execution/metric-specification

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…