diagnose_failure

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

With no annotations, the description carries the full behavioral burden. It does disclose the operating model (knowledge-base pattern matching) and the shape of the result (diagnosis, fix steps, prevention advice), which implies a non-destructive read. However, it never explicitly states read-only/non-mutating behavior, whether logs are persisted, or any auth or rate-limit constraints.

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?

Front-loaded with the core action, then a short bullet list of use cases and a returns line. Mostly tight, though the three usage bullets overlap substantially (root cause analysis vs debugging vs understanding behavior), so it is efficient but not maximally compressed.

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?

For a two-parameter, no-output-schema tool, the description usefully explains what is returned (diagnosis, fix steps, prevention advice), compensating for the absent output schema. The remaining gap is the unaddressed safety/read-only profile in the absence of annotations.

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 100%, with both required parameters ('symptoms', 'logs') clearly documented in the schema itself. The description only loosely restates them ('checks your symptoms and logs') without adding format, size, or content guidance, so the baseline of 3 applies.

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 opens with a specific verb+resource ('Diagnose errors, failures, or unexpected behavior using knowledge base documentation') and clarifies the mechanism (matching symptoms/logs against known failure patterns). It does not, however, differentiate itself from the sibling 'search_knowledge', which also operates over a knowledge base — an agent could reasonably confuse the two.

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?

It gives explicit 'Use this tool when you need' contexts: root cause analysis, debugging config/dependency problems, explaining unexpected framework behavior. That is clear when-to-use guidance, but it names no exclusions and does not route the agent away from 'search_knowledge' or toward 'verify_code_math' for adjacent tasks.

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