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Milliliters to teaspoons

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

C2.7/5.0
Behavior2/5

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

With no annotations, the description must carry full behavioral disclosure. It states that the prompt is discarded, but does not explain that all 9 parameters are validated and then discarded, nor that the output is a fixed template independent of inputs. The schema descriptions hint at this ('discarded after the shape check'), but the tool description itself is vague and potentially misleading about what happens with the 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 extremely concise, consisting of two short sentences. The key point (return a template) is front-loaded, and there is no unnecessary filler. However, the brevity borders on under-specification, which slightly detracts from its usefulness.

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?

For a tool with 9 parameters, no output schema, and no annotations, the description is inadequate. It does not describe the content of the three-step template, nor does it explain the role of the parameters (even if they are discarded). An agent would not know what the template looks like or what to expect as a result, making the tool difficult to use correctly.

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 schema description coverage is 100%, so each parameter is already documented. The description adds no meaning beyond the schema; it only mentions the prompt being discarded, which does not clarify parameter semantics. Given high schema coverage, the baseline of 3 is appropriate, but the description does not enhance understanding of how parameters influence the result.

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 states the tool returns a three-step thinking template, which is a specific verb and resource. However, it does not differentiate it from the many sibling tools, as there is no mention of when this template is appropriate or how it differs from other tools like citation or calc-eval.

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?

The description provides no guidance on when to use this tool versus alternatives. The phrase 'Prompt discarded' is confusing and does not clarify the tool's purpose or usage context. There is no mention of exclusions or conditions, making it impossible for an agent to decide when to call 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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