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

Annotations cover read-only, open-world, and idempotent behavior, and the description adds a large amount of non-obvious behavioral context: the token-overlap matcher, compatibility codes, gross-vs-net fee disclosure, skipped-leg counters, and the fact that pairing_unverified is always present. It also warns that returned pairs may still carry warnings and that temporal_alignment null means unknown, not aligned. This is exemplary transparency beyond the annotations.

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-organized with uppercase labels (TWO MODES, RESPONSE, SAFETY FIELDS) and front-loaded purpose, but it is very long and contains some redundancy, such as repeating that compatibility fields can be non-empty and that temporal_alignment_unknown differs from confirmed alignment. Every sentence adds value, but the density pushes past concise into heavy reading.

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 tool with no output schema and significant complexity, the description is remarkably complete: it explains the response shape, compatibility codes, skipped counters, fee caveats, and how to interpret null temporal fields. An agent has enough context to call the tool correctly and interpret its results without additional documentation.

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 100%, so the baseline is 3, but the description adds meaningful semantics: it explains that explicit parameters override topic-mapped sides, that both modes run the identical matcher, and it gives example ticker/slug formats. This goes beyond the schema's short descriptions without needing to restate parameter lists.

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 as a cross-venue spread calculator between Kalshi and Polymarket for the same resolving question, with specific detail about price gaps and participant pools. It is more specific than the title and clearly about spread detection, but it never explicitly distinguishes itself from the sibling polymarket_arbitrage, so it misses the full sibling-differentiation bar.

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 usage context: two modes (topic shortcuts vs explicit ticker/slug), when to read safety fields, and warns that pre-mapped topics are often not tradeable. It does not explicitly name alternatives like polymarket_arbitrage or state when NOT to use this tool, but within its own domain it provides strong mode-selection and interpretation guidance.

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