livefpl_transfer_trend_data

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly states this is a data-fetch operation producing JSON and describes the return shape (nodes and edges fields), which effectively signals a read-only behavior. It does not disclose potential caveats such as data freshness, API rate limits, or failure modes, but for a simple data tool whose main behavior is 'return structured data,' the disclosure is adequate.

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 tightly organized: a purpose sentence, a sibling-distinction sentence, a usage directive, and compact Args/Returns blocks. It is front-loaded with the core purpose and every sentence earns its place. Zero filler or redundant restatement of the tool name.

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 low-complexity tool — a single optional parameter, an output schema present, no nested objects — the description is nearly complete. It documents the parameter semantics, the return structure, and the sibling relationship. Minor omissions like top_n bounds or behavior when omitted are trivial against the simplicity of the tool.

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 does: it explains the sole parameter as 'top_n: Number of highest-volume transfer pairs to include (default 20).' This adds real meaning beyond the schema's bare integer type and default, clarifying that the value selects the N highest-volume transfer pairs. Full compensation for the single parameter at 0% coverage justifies a strong score.

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 opens with a specific verb and resource: 'Get the FPL transfer-trend node-link graph as structured DATA (JSON).' It then explicitly distinguishes itself from its sibling livefpl_transfer_trend_graph by declaring it returns 'the underlying data behind' that graph — the numbers rather than the image. This gives an agent an unambiguous, specific purpose that separates it from its close sibling 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?

It gives an explicit when-to-use directive: 'Use this when you want the numbers rather than an image,' directly naming the alternative livefpl_transfer_trend_graph. This tells the agent exactly which sibling to choose and under what condition. The selection logic is stated, not left to inference.

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