Skills evaluation
๐Ÿ“ฆ

evaluation

Content revision r2 Safe โš™๏ธ External commands

Build Reliable Agent Evaluations

Agent quality is difficult to measure because outputs vary and may have several valid forms. This skill builds repeatable rubrics, tests, gates, and monitoring.

Supports: Claude Codex Code(CC)
๐Ÿฅˆ 81 Silver

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request
Review the Skillstore skill "evaluation" from https://skillstore.io/skills/muratcankoylan-evaluation.md and its manifest at https://skillstore.io/api/skills/muratcankoylan-evaluation/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

Your Agent should still show its plan and request any confirmation required by the security policy.

Agent-readable resources

Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.

Test it

Using "evaluation". Evaluate a customer support agent that answers account and billing questions.

Expected outcome:

  • Dimensions: factual accuracy 35%, completeness 25%, policy compliance 25%, clarity 10%, tool efficiency 5%.
  • Deterministic gates: account identifiers are valid, required disclosures appear, and prohibited actions are absent.
  • Release threshold: overall score at least 0.85, with no dimension below 0.75.

Using "evaluation". Create a regression suite for a research agent.

Expected outcome:

  • Use 50 cases across simple lookup, comparison, multi-source synthesis, and ambiguous research tasks.
  • Score citation accuracy, source quality, completeness, factual accuracy, and tool efficiency separately.
  • Compare each release with the established baseline and review all significant dimension regressions.

Using "evaluation". Plan production monitoring for an agent with variable traffic.

Expected outcome:

  • Sample one percent of interactions, plus all failures and unusual tool sequences.
  • Alert when pass rate falls below 0.85 and escalate when it falls below 0.70.
  • Review trends by task type, complexity, model version, and evaluation dimension.

Security Audit

Safe
v8 โ€ข 8/9/2026 Open versioned report

All 29 static findings are false positives caused by Python mapping methods, documentation markup, ordinary prose, comments, or YAML examples. The reviewed files contain no command execution, sensitive file access, system reconnaissance, prompt injection, or other semantic security concern.

3
Files scanned
1,253
Lines analyzed
0
Review items
0
False positives ignored
No confirmed security findings were detected by the latest completed static and semantic audit. This does not prove the skill has no side effects.
Audited by: codex View Audit History โ†’
Share & cite this report

Share the versioned assessment report, neutral badge, embed card, and citations. Skillstore reports evidence without deciding whether this Skill is safe.

Open versioned report
Security Assessment

Copy report link

https://skillstore.io/skills/muratcankoylan-evaluation/audits/8?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

Markdown badge

[![Skillstore security assessment](https://skillstore.io/badges/skills/muratcankoylan-evaluation/security.svg)](https://skillstore.io/skills/muratcankoylan-evaluation?utm_source=security_passport_badge)

HTML badge

<a href="https://skillstore.io/skills/muratcankoylan-evaluation?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/muratcankoylan-evaluation/security.svg" alt="Skillstore security assessment" loading="lazy"></a>

Embed card

<iframe src="https://skillstore.io/embed/skills/muratcankoylan-evaluation.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>
Academic citations (APA ยท BibTeX ยท CFF)

APA citation

muratcankoylan. (2026). evaluation security audit report (audit version 8) [Author version unspecified]. Skillstore. https://skillstore.io/skills/muratcankoylan-evaluation/audits/8

BibTeX citation

@techreport{muratcankoylan-muratcankoylan-evaluation-2026, author = {muratcankoylan}, title = {evaluation security audit report (audit version 8)}, institution = {Skillstore}, year = {2026}, number = {8}, url = {https://skillstore.io/skills/muratcankoylan-evaluation/audits/8}, note = {Author version unspecified} }

CITATION.cff

cff-version: 1.2.0 message: "If you use this Skill, cite its author and this versioned security audit report." title: "evaluation security audit report (audit version 8)" version: "unspecified" type: report authors: - name: "muratcankoylan" date-released: "2026-08-09" url: "https://skillstore.io/skills/muratcankoylan-evaluation/audits/8" identifiers: - type: other value: "skillstore:muratcankoylan-evaluation:audit:8" description: "Skillstore immutable audit report identifier"

Compare variants

4 installable variants

Each author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.

Why this variant is first

Highest Skillstore Score
muratcankoylan Recommended Current

muratcankoylan-evaluation

Skillstore Score 81
Evidence Confidence High
Skillstore usage 11
Updated

2026-08-21

chakshugautam-evaluation

Skillstore Score 80
Evidence Confidence High
Skillstore usage 9
Updated

2026-08-21

sickn33-evaluation

Skillstore Score 78
Evidence Confidence High
Skillstore usage 11
Updated

2026-08-21

asmayaseen-evaluation

Skillstore Score 77
Evidence Confidence High
Skillstore usage 12
Updated

2026-08-21

Skillstore Score

Why this score Evidence Confidence: High
64
Architecture
85
Maintainability
87
Content
71
Community
91
Spec Compliance

What You Can Build

Gate Agent Releases

Build regression suites and quality thresholds that detect performance drops before deployment.

Compare Agent Configurations

Measure quality, token use, and tool efficiency across models, prompts, or context strategies.

Monitor Production Quality

Define sampling, alerts, and trend reports for changing agent behavior in live systems.

Try These Prompts

Define Evaluation Goals
Create an evaluation plan for [agent task]. Define success outcomes, five quality dimensions, measurable criteria, and appropriate pass thresholds.
Build a Test Set
Design 50 evaluation cases for [agent workflow]. Stratify them by complexity, include edge cases, and describe expected outcomes without requiring fixed execution paths.
Create a Quality Gate
Design a release gate for [agent system]. Separate deterministic checks from rubric scores, define dimension minimums, and specify baseline regression tolerances.
Design Production Monitoring
Create a production evaluation strategy for [agent system]. Include sampling, human review, alert thresholds, confidence reporting, drift detection, and baseline comparisons.

Best Practices

  • Measure final outcomes and quality dimensions instead of requiring one execution path.
  • Run deterministic validation before model judgment and preserve dimension-level results.
  • Use representative cases, production-realistic budgets, independent judges, and regular human review.

Avoid

  • Do not rely on one aggregate score that can hide critical dimension failures.
  • Do not build test sets only from easy, clean, or synthetic examples.
  • Do not treat evaluation as a one-time release activity without baseline tracking.

Frequently Asked Questions

What types of agents can this skill evaluate?
It supports research, creation, analysis, support, and other agents with definable outcomes and quality dimensions.
Does the skill call an LLM judge?
No. It explains when to use model judgment, while the included script uses local heuristics that you can replace.
Can I use a custom rubric?
Yes. Define dimensions, descriptions, scoring levels, and weights that match your task and risk profile.
How large should an evaluation set be?
Start with 20 to 30 cases during exploration, then use at least 50 representative cases for stronger regression signals.
How should I handle non-deterministic outputs?
Evaluate acceptable outcomes and semantic quality. Avoid requiring one exact answer or fixed sequence of actions.
Does this replace human review?
No. Use human review for edge cases, random production samples, subtle errors, and periodic validation of automated metrics.

Developer Details

License

MIT

Skillstore revision

r2

Version notice

The author did not declare a version.

Ref

02be9409c79ca1183f7844009c14d9df684d0cf9

Maintenance freshness

8/11/2026

Usage

10 downloads ยท 254 views

File structure

๐Ÿ“ references/

๐Ÿ“„ metrics.md

๐Ÿ“ scripts/

๐Ÿ“„ evaluator.py

๐Ÿ“„ SKILL.md