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

No annotations, so the description carries the full burden. It reveals one important behavioral quirk — kind=eme_analysis routes to getemeanalysis(name) rather than object get — which is valuable. But it says nothing about read-only vs mutation, return format, or that other kinds have side-effect-free semantics, leaving gaps for a 13-way dispatcher.

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?

Very short and front-loaded: the purpose sentence comes first, followed by the specific eme_analysis caveat. No filler. The line break mid-sentence is slightly awkward but not wasteful.

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 13-kind dispatcher with 10 parameters, no annotations and no output schema, the description is far too thin. It only addresses two kinds (eme_analysis and sweep via get_results), leaving the other eleven kinds' semantics, required name/name2/name3 combinations, and return shapes entirely to the schema.

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 100%, so the schema already documents all 10 parameters and enum values; baseline 3 applies. The description adds routing info for eme_analysis, but doesn't map name/name2/name3 to the remaining kinds, which is exactly the cross-parameter knowledge an agent would need.

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 first sentence states a specific verb+resource: discover properties and metadata. This distinguishes it from set_property and get_results, which are named explicitly. However, the tool actually returns many heterogeneous kinds (work_path, selection_count, homogeneity, source_list), and the description only frames it around properties, so the scope of the tool is understated.

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?

Gives an explicit when-to-use rule ('Prefer this before inventing property names for set') and names alternatives (getemeanalysis for eme_analysis, get_results for sweeps). Does not cover when-not-to-use for the other 10 kinds, so guidance is partial.

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