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

Annotations already mark this as read-only, open-world, and non-destructive. The description adds substantial behavioral detail beyond that: caching behavior ('Cached 1h at the KV level keyed on all knobs'), the 24h-move warning, diagnostics so callers can see why a segment is empty, and the rationale for excluding Fed bets. No contradiction with 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 front-loaded with the core purpose and organized by model families, knobs, and response structure. However, it is extremely dense, including per-sport α values and placeholder-slug rules, which may be more detail than an agent needs for tool selection. Some information repeats the schema (e.g., min_liquidity/max_spread_pp), so it is not fully concise.

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?

There is no output schema, so the description must explain return values, and it does thoroughly: by_segment structure, per-opportunity fields (edge_pp_net, kelly_fraction, liquidity, spread_pp), fed_note, and _diagnostics with funnel counters. It also explains how knobs affect output and mentions caching. This is complete enough for an agent to invoke and interpret results 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 100% with detailed parameter descriptions, so the baseline is 3. The description adds extra meaning by grouping knobs under 'TRADEABLE-EDGE KNOBS' and explaining nuanced behavior, e.g., min_partition_leg_kelly filters per-leg Kelly because parent-level Kelly is always 0 for partitions. This goes beyond the schema without being redundant.

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 opens with 'Scan top Polymarket markets and return opportunities where Pipeworx data disagrees with market price' – a specific verb, resource, and clear output. It also states the intended use case, 'what should I bet on today', which distinguishes it from sibling tools like polymarket_arbitrage by focusing on data-vs-market disagreements rather than pure arbitrage.

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?

It explicitly targets the 'what should I bet on today' scenario and explains that agents avoid paging hundreds of markets. It describes filtering knobs (min_liquidity, max_spread_pp) and even notes why Fed bets are excluded from ranking. However, it does not explicitly contrast with alternative tools or state when not to use this tool, so it lacks explicit exclusions.

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