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

The description goes far beyond the readOnlyHint annotation by detailing nuanced behaviors: confidence is calibrated rather than raw, null confidence has a specific fallback contract, confidence_status enumerates suppression reasons, transform emitters carry observation-preserving fields, and most rows are flagged action_hint=ignore. These are important behavioral disclosures that structure would not convey.

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 dense but front-loaded: the purpose and raw-feed warning appear in the first sentence. Every subsequent paragraph adds necessary interpretive context — filters, output fields, confidence contract, and caveats — without redundant filler. The length is justified by the tool's semantic complexity.

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?

Even with a rich output schema, the description is complete on its own: it explains what the tool lists, how to filter, what the returned fields mean, how confidence should be quoted, why some fields may be null, and which sibling tool to use for tradeable output. No critical calling or interpretation detail is missing.

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 carries the full burden, and it succeeds: it enumerates all 8 parameters, gives concrete enum values for signal_type, direction, and urgency, specifies the limit range and default, provides an asset example, and explains filter intent. This meaningfully compensates for the bare schema.

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 opens with a clear, specific verb and resource: 'List active n0brains signals with optional filters.' It immediately distinguishes itself from trade-call tools by labeling the output as '[RAW FEED — engine inputs, NOT trade calls]' and later points to get_actionable_signals for tradeable output, so an agent can tell this tool apart from its siblings.

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 states that this tool returns engine inputs, not trade calls, and instructs agents to use get_actionable_signals for tradeable output. It also warns readers to check historical_edge and action_hint before echoing any direction, giving clear operational guidance on how to interpret and use the results.

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