CtrlK
BlogDocsLog inGet started
Tessl Logo

evaluation

This skill should be used when building agent evaluation systems: deterministic checks, regression suites, multi-dimensional rubrics, quality gates, production monitoring, baseline comparison, and outcome measurement for agent pipelines.

69

Quality

85%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

70%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is well-structured with a clear workflow and good progressive disclosure, but it is somewhat long with repeated themes and its code examples are illustrative rather than fully executable. Tightening the prose and making the code snippets complete would lift the weaker dimensions.

Suggestions

Consolidate repeated guidance across Core Concepts, Detailed Topics, Guidelines, and Gotchas into a single source of truth, moving elaboration into references/metrics.md to reduce token cost.

Make code examples fully executable by defining helper functions (assess_dimension, weighted_average, load_rubric) or replacing them with concrete, runnable logic so snippets are copy-paste ready.

Trim explanatory 'because...' clauses where the reasoning is self-evident, keeping only those that change how Claude should act.

DimensionReasoningScore

Conciseness

The body is mostly efficient and does not explain basics Claude already knows, but at ~280 lines it repeats themes across Core Concepts, Detailed Topics, Guidelines, and Gotchas, and many "because..." rationales plus the Performance Drivers table add tokens that could be trimmed or relocated. It is not a 3 because not every token clearly earns its place, and not a 1 because it largely assumes competence and avoids padding with elementary explanations.

2 / 3

Actionability

It provides concrete thresholds (0.7/0.9, 0.85/0.70), sample sizes (20-30, 50+), a YAML gate config, and Python examples, but the code is illustrative — functions like assess_dimension, weighted_average, and load_rubric are undefined, so it is not fully executable. It is not a 3 because the examples are not copy-paste ready, and not a 1 because there is substantial concrete, specific guidance.

2 / 3

Workflow Clarity

The "Building Evaluation Frameworks" section gives a clear, ordered 9-step sequence with feedback-oriented checkpoints (establish baseline before changes, run on every change and compare against baseline). It is not a 2 because the sequence and its checkpoints are explicit, and not penalized for missing destructive-operation validation since this is a measurement skill.

3 / 3

Progressive Disclosure

Content is organized into clear sections with one referenced file (./references/metrics.md) that exists and is one level deep, signaled with a 'Read when' trigger; detailed metric definitions live in the reference rather than inline. It is not a 2 because references are clearly signaled and appropriately split rather than monolithic or nested.

3 / 3

Total

10

/

12

Passed

Description

100%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is strong: it lists concrete capabilities, includes explicit when-to-use guidance, and carves out a clear, distinct niche for agent evaluation systems. It reads naturally and would trigger for the right requests.

DimensionReasoningScore

Specificity

The description enumerates many concrete capabilities ("deterministic checks, regression suites, multi-dimensional rubrics, quality gates, production monitoring, baseline comparison, and outcome measurement"), matching the score-3 anchor that lists multiple specific concrete actions. It is not a level below because it goes beyond naming a domain and a few actions.

3 / 3

Completeness

It answers both what ("building agent evaluation systems" plus the enumerated capabilities) and when ("This skill should be used when building agent evaluation systems"), an explicit trigger clause equivalent to a 'Use when...' statement. It earns 3 rather than 2 because the when is explicit, not merely implied.

3 / 3

Trigger Term Quality

It covers natural terms practitioners actually say — "deterministic checks," "regression suites," "rubrics," "quality gates," "production monitoring," "baseline comparison" — giving good coverage rather than the partial list of a level-2 anchor. It is not below 3 because the keywords are natural and varied, not just generic technical jargon.

3 / 3

Distinctiveness Conflict Risk

It occupies a clear niche (agent evaluation systems) with distinct triggers unlikely to fire for unrelated skills, matching the score-3 anchor of a clear niche with distinct triggers. It is not a level below because the scope is specific rather than broadly generic.

3 / 3

Total

12

/

12

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
muratcankoylan/Agent-Skills-for-Context-Engineering
Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.