analyze_notebook_performance

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

No annotations are present, so the description carries the full burden. It discloses that the tool returns a string containing performance analysis and recommendations, which is useful. However, it does not state whether the analysis is read-only, whether it executes the notebook, or what permissions or context are required.

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 short, front-loads the purpose in a single sentence, and organizes remaining details under Args and Returns. The mention of ctx, which is not an input-schema parameter, is a minor structural downside, but overall the description is efficient and scannable.

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?

With no annotations and no output schema, the description should cover side effects and usage context more thoroughly. It explains the purpose and return value, but does not say when to use the tool, whether it mutates anything, or what conditions make it applicable. For a simple two-parameter analysis tool, this is partially adequate but leaves clear gaps.

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?

The input schema has 0% description coverage, so the description must compensate. The Args section usefully clarifies that workspace and notebook_id accept names or IDs and that ctx contains client information. However, ctx is not present in the input schema, and no format, type, or validation details are given for the parameters.

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 names a specific verb (Analyze), a specific resource (a notebook's code), and the goal (performance optimization opportunities in Fabric). It is clear about what the tool does, though it does not explicitly contrast with related siblings like validate_pyspark_code or analyze_dax_query.

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 no guidance on when to use this tool versus alternatives, no prerequisites, and no conditions under which it should or should not be called. The intended use is only implied by the name and first sentence.

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