query_library

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

Annotations already establish read-only and non-destructive behavior, but the description adds substantial behavioral context beyond that: the tracks list is truncated to limit, totals are computed exactly, ordering is computed server-side, energy is an estimate with provenance, and genre fallback is available. These details materially change how an agent should interpret and present results.

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 description is front-loaded with the core action and key rules, and most sentences carry actionable guidance. It is somewhat long and repeats the same anti-estimation theme across multiple sentences, which costs some conciseness, but the structure remains purposeful.

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?

There is no output schema, so the description appropriately explains key return fields such as total_matching, total_duration_ms, tracks, duration_display, and energy_provenance. However, for a 9-parameter tool with 0% schema description coverage, it leaves important input filters undocumented, so the overall context is only partially complete.

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% and there are 9 parameters, so the description must carry the burden of explaining them. It adds meaning for order_by values, genre fallback behavior, and limit truncation, but it does not explain artist, played, released_after, released_before, min_duration_ms, or max_duration_ms, leaving more than half of the parameters undocumented.

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 description states a specific verb and resource: search the user's music library and return matching tracks with totals. It is immediately distinguishable from the sibling tools validate_playlist, enrich_artist, and check_feasibility, which serve different purposes.

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?

It gives explicit usage rules: call before stating any fact about the library, never estimate counts or durations, use total_matching and total_duration_ms, and pass order_by for longest/shortest/highest/lowest queries. It also explains the genre fallback path and when to search again with known_genres. The guidance is unusually complete for an agent.

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