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by invok-it

get_tool_metrics

Retrieve raw performance metrics for any tool, including invocation counts, p50/p95/p99 latency, error rate, and uptime. Use these figures to diagnose performance issues and guide optimization.

Instructions

Get raw performance metrics for a tool — invocation counts, latency percentiles (p50/p95/p99), error rate, and uptime. Use this for detailed performance analysis.

For a simple reliability check with an overall score, use get_tool_quality instead.

Args: slug: The tool's slug identifier. period: Time period — "hour", "day", "week", "month", or "all_time".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYes
periodNoall_time

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses the nature of the output (raw performance metrics) and implies a read-only GET operation, but does not state side effects, authentication needs, rate limits, or pagination behavior. It adds some value by specifying the kind of data returned, but lacks depth for a tool with zero annotations.

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, front-loads the purpose, and organizes arguments in a clear list. Every sentence adds value: the purpose statement, the usage guidance, and the parameter descriptions are all relevant with no fluff or redundancy.

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?

For a tool with an output schema (the agent can see return structure elsewhere), the description covers purpose, usage, and all parameters. It does not mention error conditions or edge cases, but given the simplicity of the tool and the presence of an output schema, it is sufficiently complete for an agent to call it correctly.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate. It fully explains both parameters: 'slug' as 'The tool's slug identifier' and 'period' with explicit allowed values (hour, day, week, month, all_time) and the default. This adds meaning far beyond the raw schema types.

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

Purpose5/5

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

The description states a specific verb ('Get'), a specific resource ('raw performance metrics for a tool'), and enumerates what those metrics are (invocation counts, latency percentiles, error rate, uptime). It explicitly differentiates itself from get_tool_quality by noting the alternative is for a simple reliability check, so an agent can distinguish between the two tools without inspecting schemas.

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

Usage Guidelines5/5

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

Provides explicit when-to-use guidance: 'Use this for detailed performance analysis' and explicitly calls out the alternative tool for a different use case: 'For a simple reliability check with an overall score, use get_tool_quality instead.' This is unambiguous and covers both application and exclusion.

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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