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invokit-mcp

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by invok-it

get_tool_quality

Evaluate a tool's reliability with a 0-100 quality score based on success rate, schema honesty, and latency consistency. Identify trustworthy tools before integrating them.

Instructions

Get the quality score breakdown for a tool — an overall 0-100 score with primary signals (success rate, schema honesty, latency consistency) and secondary signals. Use this to evaluate whether a tool is reliable enough to use.

For detailed latency percentiles and raw performance data, use get_tool_metrics 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
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses the return value and its components (success rate, schema honesty, latency consistency), implying a read-only operation implicitly via the 'Get' verb. It does not explicitly state that no data is mutated, but the context strongly suggests it. It adds value by describing the output breakdown beyond the schema.

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 well-structured with a clear purpose statement, usage guidance, a sibling alternative, and parameter details. It is front-loaded with the main purpose and includes no redundant sentences.

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

Completeness5/5

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

Given an output schema exists (which likely documents the return structure), the description covers purpose, usage, parameter semantics, and routing to an alternative. It is complete for an agent to call this tool 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's Args section provides essential meaning for both parameters: slug's role and period's allowed values ('hour', 'day', 'week', 'month', 'all_time'). This fully compensates for the schema's lack of descriptions.

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 clearly states the tool retrieves a quality score breakdown for a tool, with an overall 0-100 score and primary/secondary signals. It also explicitly differentiates from sibling get_tool_metrics by mentioning that detailed latency percentiles are handled there.

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 guidance on when to use this tool ('evaluate whether a tool is reliable enough to use') and names the alternative for detailed latency data, directing to get_tool_metrics instead.

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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