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chimeraforge

chimeraforge

by Sahil170595
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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chimeraforge_resolve_model

Resolve a model ID to its actual parameters and architecture, grounding deployment planning in verified specs rather than hallucinated details.

Instructions

Resolve a model id to real params/architecture (grounds hallucinated specs).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "model": "<model>"
    },
    "name": "chimeraforge_resolve_model"
  }
}

Input Schema

NameRequiredDescriptionDefault
modelYes
hf_revisionNo
allow_networkNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.65.0
    • addedInput schema / properties / hf_revision
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Hf Revision"
+}
  2. First observed

TDQS

B3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It hints that results are grounded/real rather than generated, but omits critical behavior: that allow_network defaults to true (this call may hit the network), how hf_revision affects resolution, what happens on failure, and whether results are cached.

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?

A single front-loaded sentence with no filler; the core action and purpose come first. The parenthetical is slightly jargon-y but earns its place by conveying the anti-hallucination intent.

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

Completeness3/5

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

With no annotations and no output schema, the description should explain more about the return shape ('params/architecture' is only a gesture) and the network/revision behavior of the tool. Adequate as a minimum but leaves meaningful gaps for a 3-param resolution tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% across 3 parameters, so the description must compensate. It only loosely implies what 'model' means (a model id) and says nothing about hf_revision or allow_network, leaving two of three parameters undocumented in both schema and description.

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

Purpose4/5

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

Specific verb+resource: 'Resolve a model id to real params/architecture' clearly states the transformation performed. The parenthetical '(grounds hallucinated specs)' reinforces intent. It is distinguishable from siblings like list_hardware or compare_api, though it never names them.

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

Usage Guidelines3/5

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

The parenthetical implies the use case (verify model specs rather than trust hallucinated ones), which is a soft usage signal. However, it gives no when-not guidance, no prerequisites, and never points to an alternative among the siblings.

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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