diagnose_issue

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

No annotations provided, so the description carries the full behavioral burden. It doesn't disclose whether the tool invokes an LLM, whether it's read-only or has side effects, whether it's slow/expensive, or what form the diagnosis output takes. 'Deep root-cause analysis' is a meaningful hint but doesn't reveal operational traits.

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?

Two efficient sentences, front-loaded with the core action and then the analytical dimensions. No filler; slightly could be improved by adding when-to-use guidance without bloating.

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 single-parameter, read-like analysis tool with no output schema and no annotations, the description gives a decent conceptual overview but omits important context: expected output format, cost/latency implications, and when this supersedes simpler sibling tools. It's adequate but leaves gaps an agent would need to guess.

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% and there is only one parameter (issueId), which the schema already documents. The description adds nothing beyond what the schema provides, so baseline 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?

States a specific verb and resource ('root-cause analysis of a Sentry issue') and enumerates the analytical scope (stack trace, error patterns, frequency, platform knowledge). This clearly distinguishes it from siblings like sentry_get_issue (retrieval) and sentry_get_issue_events (raw events), which merely fetch data rather than analyze it.

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 a diagnostic use case, but offers no explicit when-to-use guidance nor names the sibling alternatives (e.g., 'use sentry_get_issue for raw data, diagnose_issue for analysis'). The 'deep' qualifier hints at escalation, but this is left to inference.

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