make_digest

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

Despite having no annotations, the description fully discloses the critical behavioral trait: the tool is not implemented. It also adds context about the server's LLM pipeline. This is more transparent than typical annotation-based disclosures.

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 extremely concise, with two short sentences. The first sentence front-loads the intended functionality, and the second immediately provides the non-implementation warning and alternative. No unnecessary words.

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 one-parameter tool with an output schema, the description is complete: it explains the intended action, states that it is not implemented, and names the alternative. This provides all context needed for the agent to handle the tool safely.

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?

The description interprets the sole parameter 'days' as 'from the last days days', adding semantic meaning beyond the schema's plain integer type and default value. However, it does not specify any constraints like valid range, which slightly limits completeness.

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 intended purpose: building a markdown digest of relevant articles using the server's LLM pipeline. It also distinguishes this tool from its siblings by explicitly naming the replacement tool (get_articles_for_digest), making the actual utility unambiguous.

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 guidance by stating 'Not implemented yet - use get_articles_for_digest instead.' This tells the agent precisely when not to use the tool and which alternative to invoke, satisfying the highest level of usage guidance.

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