mfl_free_agents

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

Annotations already declare read-only, open-world, and idempotent traits. The description adds valuable behavioral context beyond this: the exact return structure (ids only, with a join note to mfl_players for names and mfl_player_scores for form), the auth requirement (works without key; MFL_COOKIE unlocks more), and a concrete example. This goes beyond the annotations and helps the agent understand both the response and access restrictions.

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 compact: a one-sentence definition, the return shape, an example, and an auth note. It is front-loaded with the core purpose, and every line carries information without redundancy or fluff. The structure guides the agent from 'what' to 'how' to 'auth' efficiently.

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 read-only lookup tool with 6 parameters and no output schema, the description is complete: it defines the resource, gives the exact return format, provides a working example, notes auth variations, and explains how to enrich the ids (join to other tools). Combined with the well-documented schema and annotations, an agent has everything needed to call and interpret the result 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?

The schema already describes all parameters with 100% coverage, including 'Leave as-is' notes and the strong recommendation for POSITION. The description adds an example usage that clarifies how to combine year, L, and POSITION, and reinforces the recommendation with 'Strongly recommended — the unfiltered pool is large.' This adds marginal value on top of the schema, justifying a score above the baseline.

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 first sentence precisely defines the tool's purpose: 'Players not on any roster in this league — the pool an add or a waiver claim draws from.' This clearly conveys that it returns free agents, distinguishing it from roster/player lookup tools. The example further reinforces the intent.

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 gives clear context by explaining this is the pool for adds/waivers, and the example shows how to filter by position. It does not explicitly name alternatives (like mfl_rosters for rostered players), but the definition of free agents inherently signals when this tool is appropriate, which qualifies as clear context without exclusions.

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