prime_gap_sieve

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'sieve-generated primes', hinting at a computational method, but doesn't describe output format, performance characteristics, error handling, or side effects. For a tool with one parameter and no annotations, this leaves significant gaps in understanding how it behaves.

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, but the second sentence is a domain/category tag that adds minimal value. It's front-loaded with the core purpose, though slightly vague. There's no wasted verbiage, but it could be more informative without sacrificing brevity.

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 the tool's complexity (prime gap analysis), lack of annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't explain what the tool returns, how it processes the 'limit', or any algorithmic details. For a mathematical tool with siblings offering similar functions, more context is needed to guide the agent effectively.

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 input schema has 0% description coverage, with one parameter 'limit' undocumented. The description adds no information about this parameter—it doesn't explain what 'limit' means (e.g., upper bound for primes, number of gaps to analyze) or its expected range/units. With low schema coverage, the description fails to compensate, leaving the parameter's purpose unclear.

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 states the tool 'Analyze prime gaps using sieve-generated primes', which provides a verb ('Analyze') and resource ('prime gaps'), but it's vague about what 'analyze' entails (e.g., compute gaps, find patterns, or something else). It distinguishes from siblings by mentioning 'sieve-generated primes', but many sibling tools involve primes (e.g., 'prime_gap', 'prime_gaps_analysis'), so differentiation is weak. The domain/category tags add context but don't clarify the specific action.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, typical use cases, or compare it to sibling tools like 'prime_gap' or 'prime_gaps_analysis'. The agent must infer usage from the name and description alone, which is insufficient for effective tool selection.

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