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

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds valuable context: it explains the response structure (tracked, expired, snapshot_dates), the meaning of trend and decay_pp_per_day, the 60-day TTL limit, and that decay is computed from daily closes not intraday. It also explains snapshot gaps (cache-miss). This goes well beyond the annotations to disclose behavioral nuances.

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 long but well-structured with clear labels (Args, RESPONSE, LIMITS) and is front-loaded with the core purpose. Every sentence adds value about response semantics, interpretation, or limitations. While not as brief as a two-sentence description, the length is justified by the tool's complexity and the absence of an output schema.

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?

Since there is no output schema, the description carries the full burden of explaining the return values. It details the tracked[] objects (edge_pp_net time-series, first_seen, trend, decay_pp_per_day), expired[] objects (lifespan_days, median as competition clock), and snapshot_dates[]. It also covers limitations (TTL, snapshot start, daily closes). This is a complete and self-sufficient description for an agent to understand what to expect.

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 input schema already describes both parameters with 100% coverage, including defaults and valid values. The description repeats 'days (lookback, default 14, max 30)' and 'window (snapshot family, default 1wk)' but adds no new syntax or format details beyond the schema. Per the rubric, baseline 3 is appropriate when the schema does the heavy lifting.

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 it provides edge persistence and decay telemetry built from daily snapshots, and explicitly answers the question 'how long has this edge existed and is it shrinking?'. This distinguishes it from sibling tools like polymarket_edges, which likely provides current edge data. The verb+resource+scope is specific and unambiguous.

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 (when edge persistence/decay matters) and explains that it uses daily snapshots. However, it does not explicitly name alternative tools for different scenarios (e.g., 'use polymarket_edges for current edges'), so it lacks explicit when-not-to-use guidance. Still, the context is strong enough for an agent to infer appropriate use.

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