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

Goes well beyond the annotations by disclosing upsert semantics (an existing name receives the given values, so re-syncing is one call), key auto-assignment for keyless rows, skip behavior for value-less duplicates, the 500-row cap, table-state restrictions, and the token requirement. Note a mild tension with idempotentHint=false: the description implies re-sync is safe, but keyless rows still append on each call — it is not a real contradiction because keyed rows behave differently from anonymous ones.

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?

Front-loaded with the core action and row limit, then layers dedup, provenance, and table-state rules in a logical order. It is dense and somewhat run-on in the middle, but almost every clause carries operational meaning.

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?

Covers the write semantics, constraints, and auth that matter for a 2-parameter bulk mutation, which is a lot given the zero schema coverage. It does not say what the call returns (created vs updated counts), and there is no output schema to fill that gap.

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?

With 0% schema description coverage the description carries the load and mostly succeeds: it explains that `rows` accepts plain names or objects with `values` keyed by column id or label, defines `key`, and spells out the `origin` enum with its `note`/`source` companions and default. The `slug` parameter is only implied ('a table you run') and never explicitly described.

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?

Opens with a concrete verb+resource+bound: 'Add up to 500 rows to a table you run,' which immediately separates it from cell-level siblings like fill_cells or get_cell. It never names a sibling explicitly, so the differentiation is inferred rather than stated.

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 clear usage context ('so a whole tracker or dataset goes in a few calls') and concrete preconditions: rows with values can go into published tables, name-only rows only into drafts, and proof-required tables accept name-only rows. It stops short of explicitly routing an agent away from alternatives such as fill_cells when only individual cells need updating.

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