MCP Server for Splunk

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context such as the 'Security: creation is constrained by app-level permissions' and describes output ('created collection with name, fields, accelerated_fields, replicated'), but it does not cover potential side effects, error conditions, or rate limits. The description provides basic behavioral information but leaves gaps for a mutation tool.

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

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

The description is well-structured with a purpose statement, detailed parameter explanations, and security note. It is appropriately sized for a 6-parameter tool, but the 'Args:' section could be more front-loaded; the initial sentence is clear, but the bulk of information is in the parameter list, which is efficient but slightly less immediate.

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

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

Given the tool's complexity (6 parameters, mutation operation, no annotations, no output schema), the description does a good job covering purpose, parameters, and security constraints. However, it lacks details on error handling, return format specifics, or operational limits, which would enhance completeness for a creation tool in a system like Splunk.

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

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

Schema description coverage is 0%, so the description must compensate fully. It does so by providing detailed semantics for all 6 parameters, including examples and explanations (e.g., 'app (str): Target Splunk application where the collection will be created' with examples, 'collection (str): Name for the new collection (alphanumeric and underscores only)' with examples, and clear definitions for optional fields like 'fields', 'accelerated_fields', 'replicated', and 'create_lookup_definition'). This adds significant value beyond the bare schema.

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

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

The description clearly states the specific action ('Create a KV Store collection') and resource ('KV Store collection'), distinguishing it from sibling tools like 'create_config' or 'create_dashboard' by specifying it's for 'lookups or persisted configuration.' It provides a clear, non-tautological purpose that differentiates this tool from alternatives.

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

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

The description provides clear context on when to use this tool ('to provision a new collection for lookups or persisted configuration in a specific app'), but it does not explicitly state when not to use it or name specific alternatives among siblings (e.g., 'create_config' for other configuration types). The guidance is helpful but lacks explicit exclusions or comparisons.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.