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email-ish local@host shape, value discarded

by io.github.sadri-dridi
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emailish-ok

email-ish local@host shape, 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

C2.1/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It only says 'value discarded' for the email shape and does not explain side effects, network access, rate limits, or what happens for the other parameters. The schema notes 'no disk access' and 'robots-respecting' for some params, but the description itself adds almost no behavioral context.

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 short, but it is under-specified rather than concise. It front-loads a confusing phrase and omits essential information about the tool's actual function.

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 10 optional parameters, no output schema, and no annotations, the description is severely incomplete. An agent cannot determine what the tool checks, what it returns, or how to invoke it 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?

Schema description coverage is 100%, so the baseline is 3. The description adds no parameter-level meaning beyond the schema, and the tool-level description is too vague to tie the 10 parameters together into a coherent purpose.

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 'email-ish local@host shape, value discarded' is cryptic and does not state a clear verb or resource. It hints at validating an email-like shape but the tool name 'emailish-ok' and the 10 heterogeneous parameters suggest a broader validation/checking tool, so an agent cannot reliably tell what this tool does.

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 on when to use this tool versus siblings like browser-url-ok, domain-shape, or validate-json. The description does not mention any alternative or exclusion condition, leaving the agent to guess which of the many sibling tools applies.

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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