read_live_logs

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

Annotations only provide a title, so the description carries the burden of behavioral disclosure. It adds useful context about the 5-minute update cadence, which helps understand data freshness. However, it doesn't mention authentication requirements, rate limits, error conditions, or what happens when the algorithm isn't live - leaving significant behavioral gaps.

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 appropriately brief with two sentences. The first sentence states the core purpose, and the second adds important behavioral context about update frequency. There's no wasted language, though it could be more front-loaded with critical information.

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 that there's an output schema (which helps), but schema description coverage is 0% and annotations are minimal, the description is insufficient. It doesn't explain what parameters are needed, what the tool returns, or important constraints like the 250-line limit mentioned in the schema. For a tool with 5 undocumented parameters, this is inadequate.

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%, meaning none of the parameters are documented in the schema. The description provides no information about any parameters - it doesn't mention projectId, algorithmId, startLine, endLine, or format. This leaves all 5 parameters completely undocumented.

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 verb 'Get' and resource 'logs of a live algorithm', making the purpose understandable. However, it doesn't distinguish this tool from potential sibling tools like 'read_backtest' or 'read_compile' that also read logs or data, so it doesn't fully differentiate from alternatives.

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. It mentions 'snapshot updates about every 5 minutes' which gives some context about data freshness, but doesn't specify when to choose this over other read_* tools or what prerequisites might be needed.

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