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

Annotations already provide readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds valuable behavioral context beyond annotations: 'Fast: BM25 lexical search, no LLM call, no quota cost.' This discloses performance characteristics and resource implications. It also reiterates 'Read-only, no side effects', reinforcing but not contradicting 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 description is four sentences, each serving a distinct purpose: purpose, usage timing, performance, and alternative tool. It is front-loaded with what the tool does and avoids fluff. No wasted 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?

With a simple 2-parameter schema, comprehensive annotations (readOnly, openWorld, non-destructive), and a clear description covering purpose, usage, performance, and alternatives, the tool definition leaves no significant gaps. Although there is no output schema, the description's 'ranked snippets' conveys the return format sufficiently.

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 coverage is 100% and both parameters (query, limit) are adequately described in the schema itself. The description does not add extra meaning beyond what the schema already conveys; it only mentions the query type indirectly ('answering a question'), which does not materially enhance parameter understanding. Baseline 3 is appropriate given high schema coverage.

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 uses a specific verb ('Returns') and resource ('ranked snippets from the AlgoVault knowledge bundle'), and clearly scopes the domain (MCP tools, response shapes, integration patterns, code examples). It also distinguishes itself from chat_knowledge by emphasizing 'ranked snippets' vs. synthesized answers, and from other siblings by focusing on knowledge lookup.

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 explicitly tells the agent when to use it: 'Call this BEFORE other tool calls to confirm parameter usage and avoid hallucinating tool shapes.' It also names the alternative for a different need: 'For a synthesized natural-language answer use chat_knowledge.' These are clear usage directives and exclusions.

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