playlist_fill_from_search

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

With no annotations, the description carries the safety/cost burden and does substantial work: it discloses the round-robin selection algorithm, first-unseen-track winner rule, chunked adds, and a quota estimate ('len(queries) searches + chunked adds'). It does not spell out failure modes or auth/side-effect details, but the mutation is plainly conveyed by 'Grow' and 'adds'.

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?

Three compact sentences front-load the core behavior before the sibling note and quota. Every sentence carries distinct information with no filler.

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 mutation tool with no annotations and no output schema, the description plus 100%-covered schema is nearly sufficient: algorithm, cost, and the relationship to grow_playlist are present. Minor gaps are absence of an example and no statement about behavior when no query matches.

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 coverage is 100%, so the baseline is 3, and the description adds real value by explaining query cycling ('one pick per query per pass') and the pick policy ('first unseen track match wins'). The quota line also ties queries and adds to actual search count. Other parameters like market and response_format are left to the already-detailed schema.

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 opening phrase 'Grow a playlist to N items from search queries you supply' names the action, object, and data source precisely. It further distinguishes itself from the sibling grow_playlist by positioning itself as complementary ('Complements listening-data grow_playlist').

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 clear context: this tool grows a playlist from user-supplied search queries rather than listening data, and explicitly references the alternative grow_playlist. It does not enumerate explicit when-to-use/when-not-to-use conditions, so it stops short of a 5.

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