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

With no annotations, the description carries the full burden and does so richly: async semantics, exponential backoff cadence (5s→60s), expected runtimes, that only the latest version is retrievable once reanalysis starts, X-API-Key requirement, and AI-insight timing. This is exactly the behavioral context an agent needs beyond structured fields.

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 purpose and tier behavior, then flows into polling, timing, authentication. It is long, but nearly every sentence carries actionable operational detail, so waste is minimal despite the density.

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 tool with no annotations and no output schema, the description must carry the full load; it covers tiers, async status, facets, AI-insight status values, and auth. It stops short of describing the actual returned structure, but the operational coverage is strong.

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 both parameters are already documented. The description repeats the api_key fallback and the vault_id provenance rather than adding new syntax; baseline 3 applies when the schema does the heavy lifting.

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 ('Returns analysis results for a vault') and clarifies the tier-dependent scope of what is returned. It never names the closely related siblings (get-code-vault-summary, get-code-vault-reports), so an agent must infer which result-bearing tool to pick.

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?

Provides clear operational context (async, poll when status is 'processing', poll again for AI insights), which tells the agent how to use it. However, it never states when to choose this tool over the sibling summary/reports/score tools, leaving tool selection to inference.

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