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

Annotations already declare readOnlyHint/idempotentHint/openWorldHint=false, so safety is covered. The description adds value the annotations cannot: the exact output shape (Markdown table) and the full set of comparison columns, which is meaningful since there is no output schema.

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?

Two sentences, deliverable first, usage condition second. The long attribute list is dense but load-bearing because no output schema exists to convey the columns.

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 no-argument, read-only tool with a fully documented schema and no output schema, the description covers both the trigger and the returned content. The only gap is not distinguishing itself from recommend_package/quote_partnership, which an agent must resolve from names alone.

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% and the single context parameter is fully documented in the schema, so the baseline is 3. The description adds nothing about the parameter, but nothing is missing either.

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 names a specific verb (compare) and a specific deliverable (side-by-side Markdown table of ALL ELC Conference 2027 partnership packages) and enumerates the compared dimensions. This makes it trivially distinguishable from get_package (single package), list_packages (enumeration), and recommend_package (recommendation).

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?

"Use when a company weighs one partnership / sponsorship level against another" gives a clear triggering scenario. It does not explicitly exclude or name alternatives such as get_package or recommend_package, so the agent must infer the boundary, but the usage condition itself is unambiguous.

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