Iconsult MCP

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: it's a generative tool that creates a plan based on complexity assessment (using concept count, keywords, relationship density), returns structured output (step-by-step plan with tool names/parameters), and has a specific call pattern (once after match_concepts). It doesn't mention error handling or performance characteristics, but covers core operational behavior well.

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 efficiently structured in three sentences: purpose statement, complexity assessment details, and usage instructions. Every sentence adds essential information with zero waste. It's appropriately sized and front-loaded with the core functionality.

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 (generative planning with assessment logic), no annotations, and no output schema, the description does well by explaining the assessment criteria, output format, and sequencing requirements. However, it doesn't detail the plan structure or potential edge cases, leaving some gaps for a tool with behavioral complexity.

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 100%, so the baseline is 3. The description adds value by explaining that the consultation_id comes 'from match_concepts,' providing context about the parameter's origin and relationship to another tool. This semantic context goes beyond the schema's basic type/requirement documentation, though it doesn't elaborate on format or validation details.

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 with specific verbs ('generate an adaptive consultation plan') and resources ('after match_concepts'), explicitly distinguishing it from siblings by mentioning its dependency on match_concepts. It specifies what it assesses (project complexity) and what it returns (step-by-step plan with tool names and parameters).

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 instructions: 'Call once after match_concepts, then follow the generated plan.' It clearly states when to use it (after match_concepts) and what to do next (follow the plan), distinguishing it from alternatives like consultation_report or supervise_consultation by specifying its unique sequencing role.

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