Grandet

Resolve a model name / 识别模型名称

grandet_resolve_model

Read-onlyIdempotent

Look up public model identifiers when a requested name is ambiguous. Results are a page of candidates, not a cheapest-provider ranking. Prefer an exact officialId match; do not silently substitute a different model generation.

Input Schema

Name	Required	Description	Default
`host`	No	The assistant or app making this call, e.g. "claude-code" or "codex". Attribution only; it does not change results.
`lang`	No	Answer language: "en" or "zh-CN".	en
`name`	Yes	Model name text to look up, e.g. "sonnet" or "deepseek v4".
`page`	No	Result page, starting at 1.
`targetApp`	No	Catalogue ID of the app that will use the API, e.g. "openclaw", "claude-code" or "codex". Selects compatible protocols and connection steps. Send it only when the user says where the API will be used.
`skillBuild`	No	Grandet Skill build ID when called from the Skill. Omit otherwise.
`skillVersion`	No	Grandet Skill version when called from the Skill, e.g. "0.3.0". Omit otherwise.

Output Schema

Name	Required	Description	Default
`help`	No
`schema`	No
`status`	No
`candidates`	No
`pagination`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedOct 18, 2026

addedInput schema / properties / skillBuild / maxLength
```
Added value: +256
```
removedInput schema / properties / skillBuild / pattern
```
Removed value: -"^[a-zA-Z0-9._-]{1,96}$"
```

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": true,
+  "properties": {
+    "candidates": {
+      "items": {
+        "additionalProperties": false,
+        "properties": {
+          "model": {},
+          "name": {},
+          "officialId": {},
+          "sourceCount": {}
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "help": {
+      "additionalProperties": {},
+      "type": "object"
+    },
+    "pagination": {
+      "additionalProperties": {},
+      "type": "object"
+    },
+    "schema": {
+      "type": "string"
+    },
+    "status": {
+      "anyOf": [
+        {
+          "type": "string"
+        },
+        {
+          "maximum": 599,
+          "minimum": 400,
+          "type": "integer"
+        }
+      ]
+    }
+  },
+  "type": "object"
+}

First observedOct 17, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive and a closed world, so the safety profile is covered. The description adds real context beyond that: output is a page of candidates rather than a ranked answer, and ambiguous matches should not be silently substituted across generations. It does not discuss rate limits or disambiguation fallbacks.

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

Conciseness5/5

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

Three short sentences, zero filler, front-loaded with the purpose and immediately followed by the result-shape caveat and the matching rule. Every sentence earns its place.

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

Completeness4/5

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

With an output schema present and full schema coverage, the description need not explain return values or parameters; it covers purpose, result shape, and disambiguation policy for a 7-parameter tool. A note on paging behavior/termination would have closed the remaining gap.

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 every parameter (name, host, lang, page, targetApp, skillBuild, skillVersion) is already documented in the schema, including which are attribution-only and when to send targetApp. The description adds no parameter-level detail, so the baseline of 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?

Specific verb+resource: 'Look up public model identifiers when a requested name is ambiguous.' It also explicitly distinguishes itself from the sibling grandet_find_cheapest_api by stating results are 'not a cheapest-provider ranking,' so an agent can route without opening either schema.

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

Usage Guidelines4/5

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

States the triggering condition ('when a requested name is ambiguous') and the resolution rule ('Prefer an exact officialId match; do not silently substitute a different model generation'). It implicitly excludes the pricing use case by naming the cheapest-provider sibling, but does not enumerate other alternatives or say when to stop paging.

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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