Generate deterministic security hypotheses from fleet observations to guide evidence-based investigation. Converts raw asset data into testable assumptions for structured probe planning.
Generate deterministic evidence-seeking security hypotheses from fleet observations.
| Name | Required | Description | Default |
|---|---|---|---|
| assets | Yes | ||
| options | No | ||
| observations | Yes |
Changes observed during successful MCP inspections.
v1.0.0Does 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 states the output is 'deterministic' and 'evidence-seeking', which is useful, but it doesn't disclose what the generated hypotheses look like, whether the tool mutates any state, what inputs are required beyond the schema, or any side effects. For a generation tool with zero annotation coverage, this is a significant gap.
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 with no wasted words, and the key qualifiers ('deterministic', 'evidence-seeking') are front-loaded. It is appropriately concise, though it could earn a 5 by adding a brief usage note without bloating.
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?
The tool has no output schema, no annotations, and 0% parameter coverage, so the description is the only source of guidance. It explains the high-level purpose but omits what the generated hypotheses contain, how the parameters map to behavior, and how this relates to the sibling tools. An agent would struggle to invoke this correctly with only the given information.
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%, and the description does not explain the meaning of 'assets', 'observations', or 'options'. The description names the resource ('fleet observations') but doesn't clarify what 'assets' refers to or how 'options' shapes the output. With three parameters and zero schema descriptions, the description must compensate and does not.
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 ('generate') and resource ('security hypotheses from fleet observations'), and the 'deterministic evidence-seeking' qualifier adds useful specificity. It doesn't explicitly distinguish from siblings, but the resource and purpose are clear enough that an agent can infer it produces hypotheses rather than compiling or evaluating probes.
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 a use case: generating hypotheses from fleet observations. However, it provides no explicit guidance on when to choose this tool over nightmare_compile_probe or nightmare_evaluate_probe, nor any exclusions or prerequisites. The context is clear but the routing guidance is left to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.