random_numbers
[Dev] Cryptographically-secure random integers in a range (CSPRNG, unbiased) — real entropy an LLM cannot produce itself. Costs $0.001.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| max | No | ||
| min | No | ||
| count | No |
[Dev] Cryptographically-secure random integers in a range (CSPRNG, unbiased) — real entropy an LLM cannot produce itself. Costs $0.001.
| Name | Required | Description | Default |
|---|---|---|---|
| max | No | ||
| min | No | ||
| count | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the cryptographic security (CSPRNG), unbiasedness, and cost ($0.001), which are useful. However, it does not mention error handling (e.g., if min > max), any limits on parameter ranges or count, or side effects. The safety profile is partially covered but lacks detail.
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 single sentence that efficiently conveys the core purpose, security properties, and cost. It is front-loaded with the main function and avoids redundant or extraneous information.
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 simplicity (no output schema, 3 integer params with no descriptions), the description should cover default behaviors (e.g., if min is omitted, or if range is inclusive) and output format (likely an array). It fails to mention these, leaving significant gaps for an agent to understand usage fully.
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 explain the parameters. It mentions 'range' but does not connect it to 'min' and 'max', nor describe 'count' as the number of integers. An agent cannot infer the role of each parameter from the description alone, severely hindering correct invocation.
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 it provides 'cryptographically-secure random integers in a range', specifying a unique verb-resource pair. It distinguishes itself from standard LLM randomness by noting 'real entropy an LLM cannot produce itself'. Among siblings, it is distinct from 'random_pick' which picks from a list.
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 usage when unbiased randomness is needed ('real entropy an LLM cannot produce itself') but does not provide explicit guidance on when to use this tool versus alternatives, such as 'random_pick', or when not to use it. No exclusions or contextual triggers are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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