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hshen-ai

zscaler-aiguard-control-plane-mcp

by hshen-ai

get_llm_provider_by_name

Retrieve details of a specific LLM provider by entering its exact name, enabling policy and application management.

Instructions

Fetch a specific LLM provider by its exact name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
provider_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations provided; description only says 'Fetch', implying a read operation, but lacks details on error behavior (e.g., provider not found), authentication requirements, or side effects. The tool's behavior is under-disclosed.

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

Conciseness3/5

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

One short sentence, front-loaded, and free of fluff. However, it sacrifices informative content for brevity; a few more words on behavior would improve without harming conciseness.

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

Completeness2/5

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

With only 1 parameter, no annotations, but an output schema, the description should address edge cases (e.g., non-existent provider) or clarify distinction from 'get_llm_provider'. It does not, leaving the agent under-informed.

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 has 0% coverage on 'provider_name'; description adds 'exact name' hint but no further detail on case sensitivity, uniqueness, or format. Marginal improvement over raw schema.

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?

Description clearly states 'Fetch a specific LLM provider by its exact name', using a specific verb and resource, and distinguishes from siblings like 'get_llm_provider' (likely ID-based) and 'list_llm_providers' (all providers).

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?

Implicitly suggests use when needing a provider by exact name, but no explicit when-not-to-use or alternative tool mention. Siblings like 'get_llm_provider' or 'list_llm_providers' could be alternatives depending on input type.

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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