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

Annotations already cover safety (readOnly, idempotent, non-destructive), and the description adds real operational context on top: owner-only authorization, the AUTARIO_API_KEY requirement, the returned fields per proposal, a per-state count, and the overlay rule that vendor source rows are never overwritten and reads default to the source.

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 action and ordering, and the overlay paragraph earns its place by explaining read semantics. The parenthetical vendor list (Meta Ads, Google Ads, Shopify, Instagram, TikTok, Google Search Console) is enumerative padding that could be shortened.

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 supplies the return shape itself (kind, column, before/after, reason, author type, timestamp, count per state) and covers auth and access scope. Nothing an agent needs to call this read tool correctly is missing.

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 dataset_id, kind, limit and format are already documented; the description adds little beyond restating the kind taxonomy. It never mentions limit or format, so it does not compensate beyond the baseline.

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 and resource ("List the open proposals on one of your datasets") plus the four kinds it covers, matching the schema enum. It also fixes ordering ("newest first"), so an agent can distinguish it from accept_proposals/reject_proposals/list_overlays without opening another schema.

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?

Names the access precondition ("Owner only") and explicitly routes the accepted-edits case to a sibling: query_dataset overlay="with_overlay". It does not say what to do with the results (accept_proposals/reject_proposals) or when a proposal is not 'open', so it stops short of full when/when-not guidance.

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