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agentlens_analytics

Analyze agent performance, cost breakdowns, and tool usage patterns with bucketed metrics and date filters.

Instructions

Query operational analytics: metrics, costs, agent performance, and tool usage.

When to use: To understand system performance trends, cost breakdowns, agent activity, or tool usage patterns over time.

Actions:

  • metrics: Get bucketed metrics with optional range/date filters

  • costs: Get cost breakdown

  • agents: Get per-agent metrics

  • tools: Get tool usage statistics

Example: agentlens_analytics({ action: "metrics", range: "24h" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesAction to perform
rangeNoShorthand: 1h, 6h, 24h, 3d, 7d, 30d
fromNoStart date ISO
toNoEnd date ISO
granularityNoBucket granularity
agentIdNoFilter by agent ID
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It correctly indicates the tool is for querying (non-destructive) and lists actions. However, it does not disclose any additional behavioral traits such as pagination, rate limits, or authorization requirements. The absence of such details is acceptable for a simple query tool but could be improved.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured: a brief intro, when-to-use, actions list, and an example. Every sentence adds value, and it is front-loaded with the purpose. No unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 6 parameters (one required) and no output schema. The description explains the actions and provides an example, which is sufficient for a query tool. It does not explain return values, but since no output schema exists, the description could be slightly more complete regarding expected output format.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds value by explaining the 'action' parameter's options, the 'range' shorthand, and providing an example. This clarifies parameter usage beyond the schema definitions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool queries operational analytics covering metrics, costs, agent performance, and tool usage. The verb 'Query' and resource 'analytics' are specific. However, it does not explicitly differentiate from similar sibling tools like agentlens_stats, leaving some ambiguity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes a 'When to use' section that explicitly lists use cases like understanding system performance trends, cost breakdowns, etc. It provides context for when the tool is appropriate, but it does not mention when not to use it or provide alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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