title_length_outliers

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

The description states 'Read-only,' which is a meaningful safety trait, and mentions the statistical outputs. However, with no annotations provided, the description carries the full burden of behavioral disclosure. It omits details such as how saved tracks are traversed, whether title length includes spaces, how outliers are defined beyond longest/shortest, or any side effects or rate-limit implications. This is insufficient 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?

The description is a single well-structured sentence that front-loads the core purpose ('Statistical outliers in saved-track title length'), includes the key outputs (mean/median, longest/shortest), and appends 'Read-only' with no wasted words.

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 does summarize the return content, but it remains vague about format and quantity—how many titles count as 'longest' and 'shortest,' and how response_format affects the output. The optional parameters are described only in the schema, and the description does not connect them to the reporting behavior, leaving gaps for an agent to resolve.

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 each parameter is already documented. The tool description adds no additional meaning to scan_cap, max_results, or response_format beyond what the schema provides, such as how scan_cap affects outlier calculation. Baseline 3 is appropriate.

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 clearly identifies the tool's function: computing statistical outliers in saved-track title length, with mean/median and longest/shortest titles. It is specific about the resource (saved-track titles) and the computation, avoiding tautology. However, it does not explicitly distinguish itself from similar sibling statistics tools like longest_saved_tracks or shortest_saved_tracks, so it misses full differentiation.

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?

No guidance is given about when to use this tool versus alternatives. With a large sibling set containing many saved-track analysis and statistics tools, the description leaves the agent to infer the appropriate context without any explicit exclusions or alternative recommendations.

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