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

With no annotations provided, the description carries the full burden of behavioral disclosure. It thoroughly documents async behavior, tier differences, polling timing, latest-version-only semantics, authentication requirements, and the delayed availability of AI insights. This goes well beyond a minimal description.

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 long but every sentence earns its place: polling behavior, tier differences, timing expectations, status semantics, authentication, and API key fallback are all actionable. It is front-loaded with the core purpose and then layers crucial operational details without redundancy.

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 complexity of async analysis, no output schema, and no annotations, the description is remarkably complete. It tells the agent how to poll, what to expect for free vs paid tiers, how to handle missing AI insights, what happens when reanalysis starts, and how to authenticate. No critical calling information is missing.

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 coverage is 100%, so the parameters are already documented. The description adds meaningful context by clarifying that api_key is a fallback for clients that cannot set X-API-Key headers, and it ties vault_id to create-code-vault or list_vaults, which helps the agent source valid values.

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 and resource: 'Returns analysis results for a vault.' While it clearly identifies the tool's function, it does not explicitly contrast itself with sibling tools like get-code-vault-summary or get-code-vault-reports, so some ambiguity about exactly which result type this returns remains.

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 strong usage context: it explains that analysis is async, gives an explicit polling schedule with exponential backoff, and tells the agent what to do when status is 'processing' or when ai_insights is empty. It does not name alternative tools or state when not to use this tool, but the guidance is clear enough for correct invocation.

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