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

With no annotations provided, the description carries the full burden. It explicitly discloses the key behavioral trait: the limits are computed on reported venue volume, which is an upper bound, and no effective-volume adjustment is applied. It also reveals the requirement for an EnsoTrade Pro API key and notes that the adjustment was built, measured, and cut for a specific reason. This is significant behavioral context that an agent needs to avoid misusing the tool.

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 not bloated. It front-loads the core purpose and use cases, then details parameters, then adds the critical caveat. While it is somewhat long, every sentence carries useful information for an agent. A slight reorganization could tighten it, but overall it earns a high score.

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, the lack of annotations, and the 0% schema coverage, the description is remarkably complete. It covers what the tool does, when to use it, how to interpret results, parameter details, and a key caveat. The presence of an output schema means return values need not be described. Nothing essential is missing.

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. It clearly explains each parameter: `coins` (optional comma-separated list, default liquid crypto perp universe), `participation` (fraction of daily volume, default 0.10), and `limit` (number of coins, max 40). This goes beyond the minimal schema info and provides meaningful usage semantics.

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 uses a specific verb phrase ('position-limit table... sorted TIGHTEST-FIRST') and clearly identifies the resource (crypto perp positions) and the intended use cases ('what position limit should I set on X', 'rank my coins by exit risk'). It distinguishes itself from sibling tools by focusing on exit capacity within 24 hours at a participation rate, which is a unique angle compared to tools like exit_capacity or carry_pressure.

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 explicitly lists example queries ('what position limit should I set on X', 'which of my positions is too big to get out of') and provides a clear caveat about the optimistic nature of the limits. It also states that the results are computed on reported venue volume, which is an upper bound, and advises how to handle that in practice. This gives agents clear guidance on when to use this tool and how to interpret its output.

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