suggest_playlist_names

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

With no annotations supplied, the description carries the full burden and does so: it documents degradation behavior for songs_json ('不传就只能用日期/天气/心情/时段这些素材') and for weather ('取不到不影响'), states defaults for count and with_weather, and explains the name_budget constraint (11 chars when an 8-digit date prefix is added, 20 otherwise) and the purpose of recent_names (avoid repeating names on consecutive days). That is substantial behavioral context beyond a bare 'suggest names' statement.

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?

The key directive is front-loaded in bold before any parameter detail, and the per-parameter block is scannable. It is somewhat long and uses hard line-wrapping plus parenthetical asides, but nearly every line carries information an agent needs to call the tool correctly.

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 six-parameter, annotation-free tool, the description covers the purpose, the workflow, the per-parameter semantics, the return envelope fields (materials, candidates, name_budget, recent_names, note) and the length constraints. Although an output schema exists, the extra explanation of name_budget and recent_names is genuinely useful rather than redundant.

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 explains five of six parameters with real semantics: prompt as the source of mood/artist/era cues and allowed to be empty, songs_json as the song list in the same format as create_*_playlist with a stated recommendation to pass it, artists as comma-separated names, count as candidate count with default 3, and with_weather with default true. The 'date' parameter is never mentioned, 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+resource ('起名素材 + 候选名字' — naming materials plus candidate names for playlists) and explicitly contrasts itself with the built-in naming rules. It also names the downstream siblings (create_daily_playlist / create_qq_playlist) that consume its output, so an agent can place it in the pipeline without opening any 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?

Gives an explicit when-to-use rule ('给歌单起名优先用这个工具，而不是靠内置规则') plus the fallback case where built-in rules apply ('没人管时给个不重复的名字'). It also spells out the end-to-end workflow: call this tool, pick a candidate or invent one, then pass it as playlist_name to create_*_playlist.

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