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Percent-decode length, input discarded

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

D1.8/5.0
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 only states 'Query discarded,' which is a minor behavioral detail. It does not disclose whether the tool makes external calls, whether it is read-only, or how other parameters are handled. The phrase 'Query discarded' is ambiguous—does it mean only the query is discarded, or all inputs are discarded after counting?

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

Conciseness3/5

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

The description is a single, short sentence, which is concise, but it is under-specified. It does front-load the main function, but the lack of context makes it feel more like a stub than a helpful description.

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?

For a tool with 9 parameters, no required fields, and no output schema, the description is grossly incomplete. It does not explain how the tool processes the various parameters, what it returns, or how it interacts with the many 'discarded' fields. An agent cannot reliably use this tool based on the given description.

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?

Although schema coverage is 100%, the description does not clarify which parameter is the 'search query.' It adds no value beyond the schema's per-parameter descriptions, and it does not help map the parameters to the tool's purpose. The description could have specified 'the query parameter' but does not.

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

Purpose2/5

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

The description says 'Count characters in a search query,' which is a specific verb and resource, but it is ambiguous which of the 9 input parameters is the search query. It fails to identify that the 'query' parameter is the target, and it does not differentiate this tool from siblings like 'percent-decode-len' or 'memory-key-count'.

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

Usage Guidelines1/5

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. There is no mention of conditions, prerequisites, or exclusions. An agent has no idea if this should be used for validating query length or something else.

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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