get_research_briefing

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

No annotations are provided, so the description carries full burden. It discloses that the tool assembles data from 15+ sources and performs AI narrative synthesis, indicating a read operation. However, it does not mention auth requirements, rate limits, or potential side effects, making it adequate but not comprehensive.

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 two sentences plus a usage line, front-loading the purpose. Every sentence adds value, with no 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?

For a tool with three parameters and no output schema, the description covers the tool's purpose, data sources, templates, and usage examples. It could detail the output structure, but the name and description imply a briefing, which is sufficient.

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% (all three params described). The description adds context on templates and focus areas but does not significantly enhance meaning beyond the schema. Baseline of 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 clearly states the tool's function: 'Get a comprehensive investment research briefing for an NZX company.' It lists data sources (governance, financials, etc.) and mentions AI narrative synthesis. This distinguishes it from the many specific sibling tools (e.g., get_financials, get_governance_scorecard).

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 explicit usage examples ('Use for 'research report on [company]', ...') and lists four templates with contexts. It does not explicitly exclude use cases or compare to siblings, but the examples effectively guide the agent.

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