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thousandeyes-synthetic-monitoring

Manage ThousandEyes synthetic monitoring with MCP tools. Use when a user wants to list, inspect, create, update, delete, or validate synthetic tests; deploy application templates; or choose the right ThousandEyes monitoring approach across Network and Application Synthetics and Browser Synthetics.

87

1.28x
Quality

81%

Does it follow best practices?

Impact

95%

1.28x

Average score across 3 eval scenarios

SecuritybySnyk

Advisory

Suggest reviewing before use

SKILL.md
Quality
Evals
Security

Quality

Content

62%

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

This is a well-structured skill with excellent workflow clarity and logical sequencing of operations with appropriate confirmation gates. Its main weaknesses are verbosity (repeating constraints across multiple sections) and lack of concrete executable examples—all actionable guidance is descriptive rather than demonstrated. Moving detailed field mappings and test-type enumerations into the referenced files would improve both conciseness and progressive disclosure.

Suggestions

Add at least one concrete payload example inline (e.g., a sample create_synthetic_test call with actual arguments) to improve actionability without requiring reference file loads.

Consolidate repeated guidance between 'Required Behavior,' 'Workflow,' and 'Guardrails' sections—for instance, the confirmation-before-write rule appears in all three and could be stated once with a cross-reference.

Move the detailed test-type-to-field mapping (step 4.3) into reference.md and keep only a brief summary in the main skill to improve conciseness and progressive disclosure.

DimensionReasoningScore

Conciseness

The skill is fairly well-structured but verbose for what it conveys. Many points restate things Claude would naturally handle (e.g., 'do not invent tool arguments not in the schema,' 'confirm user intent first'). The extensive enumeration of test types, fields, and operations could be tightened significantly, and there is notable repetition between the Required Behavior, Workflow, and Guardrails sections.

2 / 3

Actionability

The skill provides specific tool names, field requirements, and a clear mapping of test types to their required parameters, which is useful. However, there are no concrete code examples, payload snippets, or copy-paste-ready commands—everything is described rather than demonstrated. The actual executable guidance is deferred to reference.md and examples.md.

2 / 3

Workflow Clarity

The workflow is clearly sequenced into 7 numbered phases with logical progression from discovery through confirmation to execution and reporting. It includes explicit validation checkpoints (step 4 for field validation, step 5 for user confirmation before writes), feedback loops (inspect before update if unclear, prefer instant-test before persistent changes), and handles edge cases like agent-to-agent update limitations.

3 / 3

Progressive Disclosure

The skill references reference.md and examples.md with clear signals for when to load each, which is good progressive disclosure design. However, since no bundle files are provided, we cannot verify these references exist or contain appropriate content. Additionally, the main SKILL.md itself is quite long and could benefit from moving the detailed test-type mappings and field requirements into reference.md rather than inlining them.

2 / 3

Total

9

/

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.

This is a strong skill description that clearly identifies the tool (ThousandEyes), lists concrete CRUD operations and additional capabilities, and provides an explicit 'Use when' clause with natural trigger terms. It uses proper third-person voice throughout and is concise without being vague. The description would effectively distinguish this skill from others in a large skill library.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: list, inspect, create, update, delete, validate synthetic tests; deploy application templates; choose monitoring approach. These are clear, actionable operations.

3 / 3

Completeness

Clearly answers both what ('Manage ThousandEyes synthetic monitoring with MCP tools') and when ('Use when a user wants to list, inspect, create, update, delete, or validate synthetic tests; deploy application templates; or choose the right ThousandEyes monitoring approach'). Explicit 'Use when' clause is present.

3 / 3

Trigger Term Quality

Includes strong natural keywords users would say: 'ThousandEyes', 'synthetic monitoring', 'MCP tools', 'synthetic tests', 'application templates', 'Network and Application Synthetics', 'Browser Synthetics'. Good coverage of domain-specific terms a user would naturally mention.

3 / 3

Distinctiveness Conflict Risk

Highly distinctive with 'ThousandEyes' as a specific product name and 'synthetic monitoring' as a clear niche. Very unlikely to conflict with other skills due to the specificity of the domain and tooling.

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.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
thousandeyes/thousandeyes-ai-agents-toolkit
Reviewed

Table of Contents

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