check_algo_status

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

No annotations are present, so the description must bear the full burden of behavioral disclosure. It lists what is checked but does not mention whether the operation is read-only, requires special permissions, has side effects, rate limits, or any other behavioral traits beyond the vague verb 'check'.

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 two concise sentences, front-loaded with the verb and resource, and avoids redundant phrasing. Every word adds value, and the structure is efficient.

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 has 3 optional parameters, no output schema, and zero annotations, the description covers the purpose but lacks details on return format, pagination, error conditions, and how the tool interacts with other tools (e.g., after checking, what action to take). It is adequate but incomplete for an AI agent to fully understand usage.

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 low (33%), and the description adds minimal parameter context beyond the schema's brief notes. For instance, 'symbol' is undocumented in both schema and description, and the relationship between parameters and the listed checks (e.g., schedule deviation) is unclear.

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 the action ('Check status of algo orders') and lists specific aspects checked (schedule deviation, execution quality, IS shortfall, etc.), making it unambiguous and distinguishing it from sibling tools like 'cancel_algo' or 'modify_algo'.

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 implies usage via the listed checks but does not explicitly state when to use this tool versus alternatives like 'query_orders' or 'validate_orders'. No exclusion criteria or context-specific guidance is provided.

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