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Australia/Darwin clock

think-steps

Return a three-step thinking template. Prompt 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

B3.1/5.0
Behavior3/5

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

The description discloses a key behavioral trait: 'Prompt discarded,' indicating that the input does not influence the returned template. However, with no annotations supplied, the description carries the full burden and does not explain side effects, output behavior, or what happens if parameters are invalid. It adds some transparency but not enough for a tool with seven inputs.

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 very short and front-loads the core behavior in its first sentence. The second sentence is also useful because it warns that input is discarded. It is efficient, though slightly cryptic because 'Prompt' is capitalized and no parameter of that name exists.

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

Completeness2/5

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

Given seven heterogeneous parameters and no output schema, the description is under-specified. It states the return object in general terms—'three-step thinking template'—but gives no output structure, examples, or indication of whether any parameter is ever required. An agent cannot fully determine how to correctly invoke this tool beyond guessing it is a constant-output utility.

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?

The input schema already describes all seven parameters, including the fact that each is discarded after a check, so schema coverage is high. The description adds only 'Prompt discarded,' which does not clarify how a caller should choose or populate ref, url, city, feed, host, json, or path. The description contributes no meaningful semantic value beyond the schema.

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 uses a specific verb and object—'Return a three-step thinking template'—so the core behavior is clear. The second sentence clarifies that the prompt is ignored, which helps define what the tool does not do. It does not explicitly differentiate itself from sibling tools, but none of the siblings obviously overlap with a thinking-template tool.

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?

There is no guidance about when to use this tool versus alternatives. The description implies it can be used whenever a three-step thinking template is needed, but it never states conditions, exclusions, or how it relates to sibling shape-check and fetch utilities. An agent would have to infer when to invoke it.

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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