get_context_bundle

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

Without annotations, the description discloses key behaviors: it returns a bundle with specific components, allows opt-in allocation math, and freshness=live triggers an ingest. It does not mention side effects of live mode (e.g., potential latency), but is otherwise adequate.

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: first introduces the output, second details optional parameters and freshness. It is front-loaded, concise, and every sentence adds 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 output schema exists, the description covers the main output components and optional features. The missing explanation of 'scope' is a minor gap, but overall the tool is adequately described for an agent to understand its purpose and capabilities.

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?

With 0% schema coverage, the description must compensate. It explains assets, target_pct, band, and freshness, but omits the 'scope' parameter entirely. This leaves a gap, though the other four parameters are well described.

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 returns a 'Full ContextBundle JSON' containing portfolio holdings, market, sentiment, macro, regime hints, and delta. It distinguishes from siblings by emphasizing comprehensiveness and optional allocation analysis.

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?

It explains when to use optional parameters (assets filter, target_pct/band for allocation analysis) and describes freshness modes. However, it does not explicitly compare against alternatives like get_context_at, leaving the agent to infer usage from context.

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