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Pacific/Efate clock

search-query-len

Count characters in a search query. Query discarded.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refNoGit ref name; discarded after the shape check
urlNoHTTPS URL to normalize or cite
cityNoCity name for a public weather hint; discarded after the call
feedNoPublic RSS or Atom URL; titles discarded
hostNoPublic hostname
jsonNoJSON text to validate; discarded after the check
pathNoFile path to check; no disk access
zoneNoIANA timezone name
queryNoSearch text; discarded after the length check

Schema Changelog

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

  1. First observed

TDQS

C2.8/5.0
Behavior2/5

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

With no annotations, the description carries the full burden. It discloses that the query is discarded, which is a behavioral trait, but it does not explain the fate of the other 8 parameters, nor what 'count characters' precisely returns (code points, bytes, etc.). It also fails to mention that the tool appears to perform a shape check on all provided fields, as implied by the schema descriptions. The description is misleadingly narrow.

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

Conciseness4/5

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

The description is two short sentences with the core action stated first. It is concise and front-loaded. However, its brevity borders on under-specification, which is penalized elsewhere, but for conciseness alone it is well-structured.

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

Completeness1/5

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

The tool has 9 optional parameters, no output schema, and no annotations. The description only mentions the 'query' parameter and gives no information about return values, error behavior, or the role of the other parameters. For a tool this complex, this is severely incomplete. An agent cannot reliably call it without guessing how to interpret the extra parameters and what the response will be.

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

Parameters3/5

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

Schema description coverage is 100%, so every parameter is documented with a description. The description itself adds no additional meaning beyond identifying 'query' as the primary parameter; it does not clarify why the other 8 parameters exist or how they relate to the tool's purpose. Per the rubric, baseline is 3 when schema coverage is high, and this description does not elevate it.

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 states a clear verb and resource: 'Count characters in a search query.' It is specific and distinguishes from siblings like 'memory-key-count' (which counts memory keys) and 'think-steps' (which likely counts thinking steps). However, it does not acknowledge the tool's 9-parameter schema, leaving the primary purpose somewhat narrow.

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 given on when to use this tool versus alternatives. The description does not mention context, exclusions, or alternative tools. An agent cannot determine whether to prefer 'search-query-len' over 'memory-key-count' or 'think-steps' based on the description.

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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