describe_api

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

With no annotations, the description carries the full burden and does so well. It discloses meaningful behavioral details: name resolution via dotted path or bare name, the meaning of missing doc entries, the role of undocumented_parameters, and the delegates_to/delegate_doc indirection. This goes far beyond what the input schema reveals.

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 a clear purpose sentence, then uses short, scannable paragraphs for name resolution and edge cases. Every sentence contributes actionable information; there is no filler or repetition.

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?

For a 2-parameter tool with no output schema and no annotations, the description is remarkably complete. It covers the main name semantics, the undocumented-argument pitfall, and the delegate-doc indirection. It could still explicitly describe the return shape or error behavior, but the most decision-relevant context is present.

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. It clearly explains name as a dotted path or bare name looked up in the index, and it gives practical meaning to include_source by framing it as the way to get source when documentation is missing. It does not exhaustively define include_source's output, but it adds real value beyond the 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 opening sentence is a precise verb+resource statement: it describes what a cellpy call takes and what it does, scoped to the installed package. This makes the tool's purpose immediately distinct from siblings like list_instruments, load_cell, and describe_plot_families.

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 strong procedural guidance: read undocumented_parameters before answering, use include_source=True rather than guessing, and read delegate_doc when delegates_to is set. However, it never explicitly says when to prefer this tool over alternatives like search_api, so alternative-selection guidance is left implied.

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