cancel_algo

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool cancels an algo and sends cancel requests for child slices, implying a destructive mutation. However, it lacks critical details: whether this requires specific permissions, if the cancellation is reversible, what happens to partially filled orders, or what the response looks like (success/failure indicators). For a mutation tool with zero annotation coverage, this is insufficient.

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 a single, efficient sentence that front-loads the core action ('Cancel an active algo') and adds necessary detail about child slices. Every word earns its place, with no redundancy or fluff. It's appropriately sized for a tool with 2 parameters and clear purpose.

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 complexity (destructive mutation with cascading effects), lack of annotations, no output schema, and incomplete parameter documentation, the description is inadequate. It should explain behavioral implications (e.g., idempotency, error handling) and expected outcomes. For a tool that likely impacts trading systems, more context is needed for safe agent use.

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 50% (only 'reason' has a description). The description doesn't mention parameters at all, so it adds no semantic value beyond the schema. However, with 2 parameters (one required), the baseline is 3 since the schema partially documents them. The description doesn't compensate for the coverage gap (e.g., explaining 'algo_id' format or 'reason' constraints).

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 ('Cancel') and target ('an active algo'), and specifies the secondary effect ('send OrderCancelRequest for all open child slices'). This distinguishes it from siblings like 'modify_algo' or 'release_stuck_orders' by focusing on termination rather than modification or recovery. However, it doesn't explicitly differentiate from 'cancel_replace', which might have overlapping functionality.

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 provides no guidance on when to use this tool versus alternatives like 'cancel_replace' or 'modify_algo'. It mentions 'active algo' but doesn't specify prerequisites (e.g., algo must be running) or exclusions (e.g., cannot cancel completed algos). Without such context, the agent must infer usage from the tool name alone.

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