autonomous_troubleshooter

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safe/read-only nature is known. The description additionally discloses the multi-step process (query System logs, snapshot processes, LLM analysis) and the requirement that `ctx` is needed for sampling. This adds meaningful behavioral context beyond annotations, though it could mention potential latency or failure modes.

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 phases, a return format block, an example, and notes. Every element serves a purpose, including the explicit `ctx` requirement and the return type examples. It is concise yet complete, with no fluff.

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?

The description covers the essential workflow, output format, and an example, and the output schema is defined separately. It lacks details about edge cases (e.g., empty event logs, LLM unavailability, time range of 'recent' System logs), but overall provides sufficient context for an agent to select and invoke the tool correctly.

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?

The input schema has 100% coverage for the single parameter `operation_failure`, with a clear description. The tool description adds value by placing the parameter in context through the example call and by explaining the investigation workflow, which aids correct usage. This exceeds the baseline 3.

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's purpose: 'Diagnose why a Windows operation failed using event logs, process list, and LLM sampling.' This identifies a specific verb (diagnose), resource (Windows operation), and method, distinguishing it from sibling tools that perform raw queries (e.g., winops_evtlog_query, winops_process_list).

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 a clear use case: when a Windows operation fails. It outlines the multi-phase approach, implying it should be used for end-to-end diagnosis rather than individual low-level queries. However, it does not explicitly state when *not* to use it or mention alternative tools, so it falls short of a 5.

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