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

Annotations already set readOnlyHint=true, openWorldHint=true, idempotentHint=true. The description adds valuable behavioral context beyond annotations: 'uncovered resource uris return description-only text (no fabricated data)' and '`text` is a JSON document for resource/signal ids.' This gives the agent critical expectations about output format and data limitations without contradicting the annotations.

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 section serves a purpose: Purpose, Namespaces, Triggers, When to call, Prerequisites, Next steps, Caveats, Output, Args, Disclaimer. It is well-organized and front-loaded with the most critical information. No filler or 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 tool's complexity (multiple id namespaces, output shapes, and caveats) and the minimal schema, the description is remarkably complete. It covers what the tool returns, how to invoke it for different resource types, error behavior (description-only text), and next actions. The presence of an output schema is acknowledged and the description lists the envelope fields.

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%, but the description fully compensates with a dedicated 'Args' section explaining the `id` parameter's namespace formats and examples: 'tool:{name}', 'resource:{uri}', 'signal:{market}:{symbol}'. This is far richer than the bare schema and leaves no ambiguity about the parameter's meaning.

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 function: 'standard document fetch by id from `search` results.' It specifies the resource (document), the verb (fetch), and how it relates to search, effectively distinguishing it from the sibling tools like `search` and `get_signal_detail`. The namespaces (`tool:`, `resource:`, `signal:`) further clarify scope.

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 explicit when-to-use guidance: 'Triggers: ChatGPT connectors / Deep Research call this after `search`' and 'When to call: whenever the full content behind a search result id is needed.' It also names alternatives for next steps (e.g., `get_signal_detail` / `explain_decision` for deeper evidence), clearly differentiating from other tools.

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