conflict_airdrop_distribution

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 does an unusually thorough job: it states the operation is a read ('Read'), that no prizes are claimed, that num_prizes is not recomputed, that it makes one logical GET request, that it does not auto-fetch continuation pages, that filters are forwarded as supplied without implied effectiveness, that results are locally limited to 100 rows and 256 KiB, that truncation is reported, and that oversized records are refused without partial fields. This is rich behavioral context beyond what any schema could convey.

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 dense but well-organized: it front-loads the core purpose, then covers behavioral constraints, then limits. Every sentence adds information. It is longer than ideal, but the density of useful behavioral detail justifies the length. The structure is logical: purpose → behavior → limits.

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 complexity (6 parameters, no output schema, no annotations), the description covers a lot: read semantics, id vs conflict behavior, pagination, filtering caveats, size limits, and truncation reporting. It doesn't describe the return format or the exact meaning of all parameters, but for a read-only lookup tool with this much behavioral disclosure, it is nearly complete. The main gap is parameter semantics for 'lore', 'mode', and 'order_by'.

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 for the schema's lack of parameter documentation. The description explains the semantic difference between 'id' and 'conflict' (id returns only distribution; conflict also returns conflict metadata) and mentions 'Other declared filters are forwarded as supplied.' However, it doesn't explain the meaning of 'lore', 'mode', 'order_by', or 'player' beyond the obvious, and it doesn't clarify which parameters are mutually exclusive or how they combine. The description adds some value but leaves several parameters semantically under-documented.

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: 'Read a player's recorded airdrop distribution for an explicit id or conflict.' It distinguishes the two lookup modes (id vs conflict) and notes that conflict returns metadata while id does not. It doesn't explicitly name a sibling alternative, but the distinction between id and conflict modes is clear enough to differentiate from other conflict_* tools.

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 on when to use the tool: for reading a player's recorded airdrop distribution by id or conflict. It also states what the tool does NOT do ('No prizes are claimed; num_prizes is not recomputed') and that it does not auto-fetch continuation pages. It doesn't explicitly name alternatives, but the behavioral constraints provide practical usage guidance.

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