pbi_catalog_summary

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

No annotations are supplied, so the description carries the full disclosure burden. It does add one useful behavioral signal by saying counts are over "scanned" assets, hinting the numbers depend on a prior scan rather than live data, but it says nothing about permissions, freshness, or whether the operation is read-only.

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?

A single sentence with no filler, front-loaded with the action and immediately followed by the enumerated asset types. Nothing could be removed without losing information.

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 output schema, the description usefully enumerates the categories that will be counted, effectively describing the return shape. It falls short only on whether counts reflect a cached scan or live state, which matters for interpreting the numbers.

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 tool takes zero parameters, so there is no parameter meaning to convey and the baseline of 4 applies. The description correctly does not invent filtering options that the schema does not support.

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?

States a specific verb (return counts) and enumerates the exact resources counted: workspaces, semantic models, reports, dataflows, and connectors. The word "high-level" signals an aggregate rather than a listing, which implicitly separates it from siblings like pbi_list_models or pbi_inspect_model, though no sibling is named explicitly.

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?

Usage is only implied: an agent can infer this is the orientation/overview call before drilling into specific assets. There is no statement of when to prefer it over pbi_health_audit or pbi_list_models, and no mention of preconditions such as needing a prior scan.

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