memory_recall_iterative

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

Beyond the read-only and idempotent annotations, the description reveals the internal process: decomposes query, retrieves per sub-question, and consults a planner LLM. It also discloses the output shape ('unified evidence + provenance per iteration'), which is valuable given no output schema. This provides a clear behavioral model.

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 concise, with two sentences that pack essential information. It front-loads the core functionality (iterative retrieval) and adds relevant context (multi-hop, output format). 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?

While the description explains the retrieval strategy and high-level output, it omits crucial parameter semantics and any detail about how the iterative process is configured (e.g., max_iters, k_per_iter). Without parameter clarification, an agent cannot properly invoke the tool. The description provides partial context but is far from complete.

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%, so the description must compensate by explaining parameters. It does not mention project, llm_model, max_iters, or k_per_iter at all. Even the required 'query' parameter is only implied, not clarified. This is a critical gap for usability.

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 purpose: IRCoT-style iterative retrieval. It distinguishes itself from simpler recall tools by emphasizing decomposition into sub-questions and multi-hop suitability. The verb 'retrieves' and the process description make the function explicit.

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?

Explicitly notes 'Best for multi-hop questions,' giving a clear when-to-use condition. While it doesn't name specific alternatives, this guidance differentiates it from single-hop recall tools. The reference to iterative planning further signals when this is appropriate.

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