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

Beyond the readOnlyHint/openWorldHint annotations, the description discloses cost ('Bills 3 metadata units', '0.005 credits per call'), auth behavior ('works with no credentials up to 1 call(s)/day per address'), and the underlying endpoint. These are exactly the operational facts an agent needs before invoking, and none are available in 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 core purpose is front-loaded in the first sentence, with cost/auth/endpoint details compressed into one parenthetical. It is dense but every clause carries information; the endpoint URL is arguably redundant but harmless.

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?

With no output schema, the description usefully characterizes the return value ('system prompt + structured context block') and adds cost and auth limits. It is nearly complete for a read-only, two-parameter tool, with the only real gap being the undocumented token_budget control.

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% for 2 parameters, so the description must carry the burden. It only implies the 'ticker' parameter via 'scoped to one ticker' and says nothing about 'token_budget' — its default of 6000, its 1000-16000 range, or what increasing it does. Half the parameters remain unexplained.

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 states a specific verb and deliverable ('Returns a system prompt + structured context block, scoped to one ticker'), which is a distinct artifact no sibling tool produces. An agent can identify this as the LLM-grounding tool versus the raw data tools (news, fundamentals, filings) without opening the schema.

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 gives a clear usage context: 'Drop it into OpenAI/Anthropic/any LLM SDK to ground your chatbot in current Deep Values data.' That tells the agent when this tool is the right choice, but it names no alternatives and no explicit 'when not to use' condition (e.g. for raw data retrieval, use fundamentals/news instead).

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