get_market_orderbook

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

With no annotations, the description carries the full disclosure burden. It signals a read-only retrieval and enumerates return fields (bids, asks, mid, spread bps, OBI), but does not cover error behavior for unknown markets, whether the book can be empty, data freshness/realtime status, or rate limits.

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?

Two sentences with zero filler: the first establishes what is retrieved and from where, the second enumerates outputs. It is front-loaded and appropriately sized for the tool's scope.

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 usefully enumerates the return fields, which is the key missing structured information. It falls short only on edge cases like empty or invalid markets and data freshness, which matter for a market-data tool.

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 all three parameters (including depth bounds and the venue enum) are already documented in structured fields. The description adds little semantic detail beyond the venue list, which duplicates the enum, so the baseline 3 is appropriate.

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 gives a specific verb and resource ('Retrieve normalized Level 2 orderbook depth') and enumerates the supported venues, so an agent immediately knows this is the orderbook data tool. It does not explicitly contrast itself with siblings like search_prediction_markets or scan_arbitrage_opportunities, but the resource is distinct enough to avoid confusion.

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?

There is no statement of when to use this tool versus the alternatives; the sibling set includes market search, arbitrage scanning, and fee calculation, but none are mentioned. The agent must infer that this is for reading depth data rather than discovering markets or opportunities.

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