analyze_for_recall

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

With no annotations, the description must carry the safety and behavior burden. It does disclose the output contract and the ValueError condition, which is helpful, but it does not state whether the tool is read-only, whether it performs side effects, or any auth/rate constraints.

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 a compact docstring: one summary sentence plus Args/Returns/Raises sections that each add useful 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 a single required parameter, an output schema, and an enumerated return dict, the description is nearly complete for invocation. It is only slightly incomplete by not explaining how this tool fits with siblings such as analyze_message or search_memory.

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?

Input schema coverage is 0%, so the description's 'message: User message text' is the only semantic guidance. It clarifies that the parameter is the user's message text, but adds no constraints or format details; this is adequate but minimal for a single string parameter.

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 opening line 'Analyze message for recall/search intent' names a specific verb, resource, and intent. This clearly separates it from the generic sibling analyze_message, and the returned should_search field confirms the recall-specific purpose.

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 implies when to use it: when a message needs recall/search intent analysis. However, it never names alternatives like analyze_message or says when not to use this tool, so routing decisions are left to inference.

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