ds_get_latest_failure_log

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

No annotations are provided, so the description carries the full burden. It discloses the tool's behavior: it fetches from the latest failed instance, combines three operational steps, and includes per-step error handling ('v2.0.10: Added per-step error handling — returns partial diagnostic info even if some steps fail'). While it does not explicitly state read-only status or discuss limits, the fetch intent and detailed return structure provide strong transparency.

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 well-structured with an opening summary, a version note, an Args block, and a Returns block. Every part serves a purpose, though the return schema makes it somewhat lengthy. The layout is front-loaded with the primary function, which aids quick comprehension.

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 no annotations and no output schema, the description is remarkably complete: it states the purpose, the composed steps, error behavior, all parameter meanings, and a detailed return structure. The only minor gap is the lack of explicit guidance on when not to use it, but overall it provides a thorough context for an AI agent.

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?

With schema description coverage at 0%, the description compensates by providing an Args section: 'project_name: Project name', 'workflow_code: Process-definition code', and 'log_limit: Lines of log to fetch per failed task (default 500)'. This adds meaningful semantics beyond the empty schema titles, especially clarifying log_limit's purpose and default value.

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 tool fetches all failed task logs from the latest failed instance ('One-click fetch of all failed task logs from the latest failed instance.'). This specific verb+resource differentiates it from sibling tools like ds_get_task_log and ds_list_task_instances by combining multiple steps and targeting the latest failure.

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 explains the tool is a shortcut for common troubleshooting ('Combines 3 common troubleshooting steps'), clearly indicating when it is useful. However, it does not explicitly mention when not to use it or suggest alternatives, though the combination of steps implies a quick-retrieval scenario.

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