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

The description adds behavioral context beyond the annotations by stating the required call order (get_database_schema before get_query_patterns) and the timing (before writing SQL). This explains how the tool operates within a larger workflow, which is valuable for an AI agent. The annotations already indicate this is read-only and idempotent, and the description complements these without contradicting them.

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 two sentences and front-loaded. The first sentence immediately states the purpose and examples, and the second covers prerequisites and usage timing. Every sentence adds meaningful guidance with no filler or repetition of the schema or annotations.

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 low complexity (0 parameters, no nested objects) and the existence of an output schema, the description fully covers the necessary context. It explains prerequisites, timing, and typical user intents, and there is no missing guidance for an agent to invoke the tool correctly.

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?

There are zero parameters, so the input schema is trivially complete. The description doesn't need to explain parameters, and the baseline for 0-parameter tools is 4. The description could theoretically mention what the workflow loads, but it already does, so no additional parameter semantics are necessary.

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 tool's purpose with a specific verb ('Load') and resource ('screening workflow'), and elaborates on its use for finding, filtering, scanning, and ranking stocks. It also distinguishes this from sibling workflow tools by providing concrete query examples like 'find stocks that...' and 'top 10 by...'.

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 gives explicit when-to-use guidance: 'Call BEFORE writing SQL when the user asks to find, screen, scan, rank, or filter stocks'. It also specifies a mandatory prerequisite sequence ('REQUIRES get_database_schema then get_query_patterns to be called first'). While it doesn't explicitly name when-not-to-use alternatives, the examples and workflow context make the intended usage clear.

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