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

Annotations already provide readOnlyHint, openWorldHint, and idempotentHint, which align with the description's 'analyze' language. The description adds value by disclosing data sources (GitHub issues/PRs, Snyk vulnerabilities) and the structured nature of the output, but it does not detail limitations, rate limits, or async behavior beyond the schema.

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 three sentences and front-loaded with the primary purpose. Each sentence adds relevant information: what it does, what data it ingests, and what the user needs to provide. It is slightly verbose but retains every sentence with value.

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 complexity (6 params, output schema present), the description covers the purpose, data sources, and input requirements. It does not need to explain return values because an output schema exists. Minor gap: no explicit mention of when to use async or optional snykToken, but the schema covers that.

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%, so all parameters are documented in the schema. The description only loosely references 'repository details and time range' without adding new semantic meaning beyond what the JSON schema already provides for repo, since, until, and tokens. Baseline 3 is appropriate.

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 uses a specific verb ('analyze') and clearly defines the resource: team's MTTR broken down into root causes. It distinguishes itself from siblings like dora_metrics_deep_dive by focusing on MTTR attribution (code, infra, process) and specifying data sources (GitHub, Snyk).

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 the tool is for CTOs wanting to analyze incident response efficiency via MTTR breakdown, and it states the required inputs. It provides context but does not explicitly name alternatives or when not to use this tool versus siblings such as change_failure_root_cause_classifier.

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