diagnose_sync_failure

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It states it aggregates multiple data sources and provides suggestions, but critically does not disclose that it likely performs a read-only diagnostic operation nor whether it consumes significant resources by fetching logs across multiple resources. It also doesn't reveal what specific output format or how findings are structured beyond 'actionable suggestions.' For a tool with zero annotation coverage, more behavioral detail is warranted.

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 concise and efficiently structured - two sentences covering purpose and method. It front-loads the core purpose (diagnose why sync failed) before describing what it aggregates. Every sentence earns its place without fluff or repetition. The brevity is appropriate though slightly marginal given the missing parameter guidance.

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 tool's diagnostic complexity (aggregating multiple data sources), the description could be richer, but an output schema exists. The description covers what it does and what it provides (root cause + suggestions). However, it doesn't explain how it differs from simply calling get_application_status and get_application_logs separately, nor when to prefer this over the raw data tools. For a diagnostic tool, the description is adequate but leaves room for more guidance on when to use it.

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%, and there are no parameter descriptions beyond the raw schema text still being incomplete (the schema shows 'name' and 'instance' but the coverage metric says 0% because no description field text that adds nuance). The description mentions 'application' but doesn't explain that 'name' is the application name and 'instance' is which ArgoCD instance to query. The description adds zero value for understanding parameters; with 0% coverage, it should explicitly clarify the parameter semantics but does not.

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: diagnosing why an application sync failed, with a specific verb (diagnose) and resource (sync failure). It mentions aggregation of status, conditions, events, and logs to identify root cause. However, it doesn't explicitly distinguish from siblings like get_application_status or get_application_logs, which it also draws upon. The action and scope are clear, but sibling differentiation requires inference from the 'root cause + suggestions' framing.

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 implies this is the go-to tool when a sync has failed and you need diagnostics rather than raw data. It mentions consolidating multiple data sources, hinting it should be used instead of individually querying status and logs. However, there is no explicit when-to-use vs alternatives guidance, no exclusions, and no mention of when the generic get_application tools would be preferred. Usage context is implied but not explicitly articulated.

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