recommend

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

With no annotations present, the description carries the full burden and does so well: it discloses the exact scoring algorithm, that zero-score entries are dropped, the tie-break preference order (models over datasets/benchmarks/tools/orgs, then downloads), and that results carry `score` and `why`. This is unusually rich behavioral disclosure for a tool with zero annotation coverage.

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 purpose and scoring rule, then grouped parameter notes, then a concrete example. The scoring and tie-break sentences earn their place, though the parameter list is a bit dense and could be tightened.

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 6-parameter filtering+ranking tool with an output schema, the description covers the ranking logic, filter semantics, and return fields (`score`, `why`), so an agent has almost everything needed. The undocumented `limit` default of 3 is the one remaining 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?

Schema description coverage is 0%, so the description must compensate, and it documents five of six parameters with real semantic detail (allowed dialect values, the three-state on_device semantics, license_filter exact-match behavior, type as an exact entry type). It omits the `limit` parameter entirely, leaving one gap.

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 ('Recommend entries from the Arabic AI Atlas') plus the ranking behavior, which is enough to separate it from the sibling tools search and get, which are lookup tools. An agent can tell this is a ranked-recommendation tool without opening the 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?

The description gives concrete guidance on how to drive the tool: the scoring formula (task +3, dialect +2, notes +1), tie-breaking rules, and per-parameter usage including a worked example. It does not explicitly state when to prefer this over the siblings search/get, so it falls short of full when/when-not routing.

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