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Centiliters to liters, number discarded

by io.github.sadri-dridi
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cl-l

Centiliters to liters, number 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
websiteNoPublic https website (homepage domain) to check for agent readiness: robots.txt, llms.txt, sitemap.xml, extractable HTML. Bounded, identified, robots-respecting.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / website
      Added value: +{
+  "description": "Public https website (homepage domain) to check for agent readiness: robots.txt, llms.txt, sitemap.xml, extractable HTML. Bounded, identified, robots-respecting.",
+  "type": "string"
+}
  2. First observed

TDQS

D1.4/5.0
Behavior1/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure, but it only says 'number discarded' without explaining side effects, read/write nature, network/disk access, output format, or what 'discarded' means. Some parameter descriptions hint at behaviors (e.g., 'no disk access', 'robots-respecting'), but the tool-level description does not.

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

Conciseness2/5

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

The description is very short, but it is under-specified rather than concise. It consists of a cryptic phrase that does not explain the purpose, inputs, outputs, or context. There is no useful front-loading, and every word adds confusion rather than clarity.

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?

This is a complex tool with 10 parameters, no annotations, and no output schema, so the description must provide substantial context. Instead, it offers only an unclear fragment. It does not explain what the tool returns, how the many inputs are used, whether any external access occurs, or how it differs from sibling tools. The description is critically incomplete.

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 each of the 10 parameters has a description. The tool description itself adds no parameter-level meaning and does not connect any parameter to the claimed centiliters-to-liters conversion. The baseline of 3 applies because the schema fully documents the parameters, but the description fails to enrich them.

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

Purpose1/5

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

The description 'Centiliters to liters, number discarded' merely restates the tool name cl-l and does not provide a clear verb+resource statement of what the tool does. It is also inconsistent with the schema, which contains 10 unrelated string parameters (ref, url, city, feed, etc.) that have nothing to do with a centiliters-to-liters conversion. This is a tautological and misleading purpose statement.

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 usage guidance is given. The description does not say when to use this tool, when not to use it, or how it relates to sibling tools such as calc-eval, normalize-url, or web-fetch. An agent has no way to decide between cl-l and its alternatives based on this 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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