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snake_case segment count, value discarded

by io.github.sadri-dridi
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snake-n

snake_case segment count, value 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

D1.7/5.0
Behavior1/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states 'value discarded' which hints that inputs are not retained, but it does not disclose whether the tool is read-only, has side effects, requires permissions, or what it returns. This is far below what is needed for a tool with no annotation safety profile.

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 extremely brief, but brevity is not conciseness when it fails to convey essential meaning. The one-line phrase provides almost no utility to an agent, so it does not 'earn its place'.

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?

With 10 optional parameters, no output schema, no annotations, and a one-line description, the tool is grossly under-specified. There is no explanation of the tool's overall behavior, how parameters are used together, return values, or when to invoke it. An agent would have to guess, making the description completely inadequate.

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 coverage is 100% and each parameter has a specific description (e.g., 'Git ref name; discarded after the shape check', 'HTTPS URL to normalize or cite'). These individual descriptions are clear, but they do not connect to the tool's stated purpose of counting snake_case segments. The tool description adds no parameter-level information, so the baseline of 3 is appropriate.

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 'snake_case segment count, value discarded' is a noun phrase that restates the tool name without specifying a verb or resource. It does not say what the tool does with its ten input parameters, nor does it distinguish itself from siblings like validate-json or normalize-url. The purpose is only vaguely implied and not actionable.

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?

There is no guidance on when to use this tool versus any of the 29 siblings. No context, exclusions, or alternative tools are mentioned. An agent has no basis to decide if snake-n is appropriate for a task.

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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