Katzilla MCP

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

Annotations provide readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, covering safety and idempotency. The description adds valuable context beyond annotations: it specifies the return format ('Katzilla envelope'), explains quality scoring ('freshness/uptime/confidence'), and details citation components ('source URL, license, SHA-256 hash'), which helps the agent understand output behavior and data provenance.

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 front-loaded with the core purpose in the first sentence, followed by filtering details, source information, and return format explanation in a logical flow. Each sentence adds value without redundancy, making it efficient and well-structured for quick comprehension.

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, annotations, output schema), the description is complete: it covers purpose, filtering, data source, update frequency, and detailed return format. With annotations providing safety hints and an output schema presumably detailing the Katzilla envelope, no critical gaps remain, making it fully adequate for agent use.

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 100%, with each parameter well-documented in the schema (e.g., query, forms, dates, pagination). The description mentions filtering by 'keyword, form type, and date range,' which aligns with parameters but does not add significant semantic details beyond the schema. Baseline 3 is appropriate as the schema handles most parameter documentation.

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 explicitly states the verb ('Search'), resource ('SEC EDGAR for company filings'), and scope ('10-K, 10-Q, 8-K, etc.'), making the purpose specific and clear. It distinguishes from siblings by focusing on SEC filings, unlike other government tools (e.g., congress-bills, federal-register), and the title 'SEC Edgar' reinforces this distinction.

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 implies usage context by listing filterable fields (keyword, form type, date range) and mentions the data source and update frequency, which suggests when to use it for current SEC filings. However, it does not explicitly state when not to use it or name alternative tools for similar data, leaving some ambiguity about tool selection.

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