livefpl_price_fallers

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 explains the return format ('JSON array of players with progress_now_pct, prediction_pct, per_hour_pct and predicted_new_cost') and the meaning of the threshold parameter, including the use of 1.0 to indicate actual price drops. This gives the agent a good model of what the tool does and what to expect, though it omits any mention of data freshness or rate limits, which are minor for a list operation.

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 well-structured with an Args/Returns format, making it scannable. It is not overly verbose; every sentence serves a purpose. The purpose statement is front-loaded, and parameter details are concise but complete. It could be slightly tighter, but the structure is effective and clear.

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?

Given the tool's moderate complexity (4 parameters, all optional) and the presence of an output schema, the description covers the essentials: purpose, parameter semantics, and return format. It does not describe sorting direction explicitly (though 'sorted by predicted progress' implies descending), nor does it mention edge cases like empty results. These are minor gaps. Overall, the description provides sufficient context for an agent to call the tool correctly.

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 0%, so the description must fully compensate. It does so admirably: each of the four parameters (limit, position, team, threshold) is explained with its type, default value, and behavioral effect. For threshold, it even provides a concrete example ('Use 1.0 to only show players predicted to actually drop price tonight'). This adds substantial meaning beyond the bare schema and is essential for correct invocation.

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 states the tool's purpose: 'List FPL players most likely to FALL in price, sorted by predicted progress.' It uses a specific verb ('List'), a specific resource ('FPL players'), and explicitly scopes to fallers, distinguishing it from the sibling livefpl_price_risers. The sorting mention adds useful precision.

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 provides parameter usage guidance (e.g., threshold semantics) but does not explicitly state when to use this tool versus alternatives. There is no mention of livefpl_price_risers or other siblings, nor any conditions that would make this tool the preferred choice. The agent must infer selectivity from the name alone, which is insufficient for a potential decision between fallers and risers.

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