get_epistemological_report

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

No annotations are provided, so the description carries full burden. It discloses the tool's output components ('language hard stops, canonical frame detection, auto-critique, confidence decay calculation, and recommendations'), which adds valuable behavioral context. However, it doesn't cover critical aspects like error handling, performance characteristics, or side effects, leaving gaps for a tool with no annotation support.

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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by output details and usage guidance. Every sentence adds value, though the 'Args' and 'Returns' sections are somewhat redundant with the schema and could be integrated more smoothly.

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 (epistemological analysis), no annotations, and an output schema exists (so return values needn't be explained), the description does reasonably well. It covers purpose, usage timing, and output components. However, for a tool with 0% schema coverage and no annotations, more parameter details and behavioral context would improve completeness.

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 compensate. It lists both parameters ('document_id: ID of the document to analyze' and 'query: The research question or claim being investigated'), adding basic semantic meaning beyond the bare schema. However, it doesn't provide format details, constraints, or examples, leaving significant gaps in parameter understanding.

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 the tool's purpose: 'Generate complete epistemological analysis before making scholarly claims.' It specifies the verb ('generate') and resource ('epistemological analysis'), and distinguishes it from siblings by focusing on comprehensive pre-analysis. However, it doesn't explicitly differentiate from all 30+ sibling tools, which slightly limits precision.

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 explicit usage guidance: 'Use BEFORE any complex textual analysis.' This clearly indicates when to use the tool (as a preparatory step) and implicitly suggests alternatives (other tools for analysis itself). The timing directive is specific and actionable.

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