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inite-ai

ideaudit-tools

Official
by inite-ai

compute_search_velocity

Calculates a search velocity score (0-25) from monthly Trends values, rising queries count, and geographic reach to gauge market momentum.

Instructions

Compute search_velocity_score (0-25) from Trends timeline values + rising queries count + geo region count.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
geoRegionCountNo
timelineValuesYesMonthly Trends values 0-100 (e.g. last 10-12 months).
risingQueriesCountNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full burden but only says a score is computed from inputs. It does not disclose how inputs are combined, missing-value behavior, or any side effects, leaving the tool's behavior largely opaque.

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 a single front-loaded sentence that conveys action, resource, inputs, and output range with no filler or redundancy. Every word earns its place.

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

Completeness3/5

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

For a simple compute tool, naming all inputs and the output range is enough for a basic call. However, the absence of an output schema, annotations, and any guidance distinguishing this from compute_search_velocity_v2 leaves meaningful gaps.

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

Parameters2/5

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

Schema coverage is only 33%, and the description mostly restates the parameter names in readable form ('Timeline values', 'rising queries count', 'geo region count') without adding units, defaults, roles, or computation details. The output range is helpful, but parameter meaning is not meaningfully expanded.

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 identifies the operation (compute) and resource (search_velocity_score), enumerates all three inputs, and states the 0-25 output range. However, it does not differentiate this tool from the sibling compute_search_velocity_v2, so it misses the top tier.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives, especially compute_search_velocity_v2. The description states what it computes but gives no context for choosing it over the many sibling compute_* functions.

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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