testneo_generate_tests_from_context

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

With no annotations, the description carries the full burden of behavioral disclosure. It fails to mention what the tool produces (e.g., returns test cases? saves them? side effects?). It discusses auth and route maps but omits the outcome of the generation process.

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 front-loads the core purpose, but the second half dives into low-level configuration details that could be placed in the schema. It is somewhat verbose for a description, with three paragraphs covering many edge cases.

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?

The tool has 16 parameters, nested objects, and no output schema. The description does not explain the return value or the overall effect (e.g., do tests get saved or just returned?). It lacks completeness for an AI agent to reliably invoke it.

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?

With only 6% schema description coverage, the description must compensate. It explains auth_preamble and context resolution well, but ignores most of the 16 parameters (e.g., test_types, max_tests, focus_areas). Thus it adds value on a few key parameters but leaves many others undocumented.

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 that the tool generates NLP test cases from an existing unified context, which distinguishes it from context-creation tools like testneo_ingest_figma_context. However, it does not explicitly differentiate from other test-generation tools like testneo_figma_to_tests_workflow, so the distinction is slightly opaque.

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 explicit guidance on when to use this tool (after resolving context via list or get), when not to use it (public/no-login apps omit auth_preamble), and suggests alternative tools for custom route mapping (testneo_set_project_route_map). This is comprehensive.

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