propose_hypothesis

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

With no annotations, the description carries the full burden. It discloses the output shape ('ranked hypotheses with rationale and suggested next steps') and that results are grounded in documentation, but says nothing about side-effect profile (read-only/advisory), determinism, latency, or prerequisites for the knowledge base. Adequate but leaves real gaps for a no-annotation tool.

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?

Purpose is front-loaded, but the phrase 'backed by documented framework patterns and best practices' appears twice and the bullet list largely restates the opening paragraph. The redundant content costs space without adding new selection signal.

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 appropriately describes return values (ranked hypotheses, rationale, next steps), and both simple string parameters are covered. For a two-parameter advisory tool this is nearly complete, missing only explicit read-only/advisory confirmation.

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 100%, so both parameters are fully documented in the schema, giving a baseline of 3. The description adds only loose framing ('ranked by fit for your use case') and no format or syntax guidance for current_status or recent_experiments beyond what the schema states.

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?

States a specific verb+resource: 'Propose ranked approaches or solutions based on knowledge base documentation,' which distinguishes it from retrieval siblings like search_knowledge or get_page. However, it never names or contrasts a specific sibling (e.g., build_plan, diagnose_failure), so the differentiation is inferable rather than 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?

Provides clear context with a 'Use this tool when you need' block covering ideation and ranked alternatives. It stops short of exclusions or alternatives (no 'use build_plan instead when...'), so the agent must infer boundaries against the planning/diagnosis siblings.

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