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Scopeweb

by io.scopeweb
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score_name

Read-onlyIdempotent

Use this when the user is choosing between names, or asks whether a name is any good. Not for deciding availability, which is check_live. Grade candidate names on measurable properties of the string: length, syllables, pronounceability (the radio test), presence in a published English word list, edit distance to major brands, hyphens/digits, and TLD perception. Read-only. Cannot spend money. Every component returns its score, weight and basis so the number can be audited rather than trusted. Severe properties CAP the total instead of being averaged away — a name one edit from a major brand cannot score well however short it is. EXPLICITLY NOT a search-ranking prediction: exact-match-domain SEO value has been largely dead since Google's 2012 EMD update and nothing here forecasts how a name will rank. NOT a trademark search: brand_collision is string similarity to a published list, not legal clearance. Components that cannot be measured (zone rarity, trademark) are returned as unavailable with reasons and never estimated.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainNoA single domain, e.g. 'forge.com'
domainsNoUp to 10 domains; returned ranked best-first

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultsYesScored names, highest first, each showing its working.
score_versionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "results": {
+      "description": "Scored names, highest first, each showing its working.",
+      "type": "array"
+    },
+    "score_version": {
+      "type": "integer"
+    }
+  },
+  "required": [
+    "results"
+  ],
+  "type": "object"
+}
  2. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already cover the safety profile (readOnlyHint, idempotent, non-destructive, openWorld=false), yet the description still adds material behavioral context: no spending, score/weight/basis per component for auditability, severe properties CAP the total rather than averaging, and unmeasurable components returned as unavailable rather than estimated. This is substantive disclosure that annotations cannot express.

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?

Front-loads usage and the sibling exclusion before moving to behavioral caveats, and each sentence carries distinct information. It runs long and some sentences are dense, but none are filler or repetition of the name.

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

Completeness5/5

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

An output schema exists, so return structure need not be explained, and the description instead supplies the scoring model, the capping rule, and the explicit non-claims. For a read-only scoring tool with this complexity, nothing an agent needs in order to call or interpret it is missing.

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 both 'domain' and 'domains' (single vs. up to 10, ranked best-first) are already fully documented in the schema. The description adds no parameter-level syntax or format detail beyond what the schema provides, so the baseline 3 applies.

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

Purpose5/5

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

States a specific verb and resource ('grade candidate names on measurable properties of the string') and enumerates the actual dimensions scored. It explicitly distinguishes itself from the nearest sibling by name ('Not for deciding availability, which is check_live'), so an agent can separate them without opening schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit trigger ('when the user is choosing between names, or asks whether a name is any good'), an explicit exclusion routing to the alternative ('check_live'), and two further scope exclusions (not a search-ranking prediction, not a trademark search). Nothing about when to select this tool is left to inference.

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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