artefact-mcp-server

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

Annotations indicate readOnlyHint=true, destructiveHint=false, openWorldHint=true, and idempotentHint=true, covering safety and idempotency. The description adds value by specifying that it 'scores clients', 'segments them', and 'extracts ICP patterns', which clarifies the analysis behavior beyond just reading data, though it doesn't detail rate limits or specific auth needs.

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 well-structured and concise, with a clear purpose statement followed by bullet-like sections for Args and Returns. Every sentence adds value without redundancy, making it easy to parse and front-loaded with key 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 complexity (analysis with segmentation and pattern extraction), annotations provide safety and idempotency info, and an output schema exists (mentioned in Returns), the description is complete enough. It covers purpose, parameters, and return structure adequately without needing to duplicate schema details.

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 full burden. It effectively explains both parameters: 'source' as data source options and 'industry_preset' as scoring preset options with examples, adding meaningful context beyond the bare schema. However, it doesn't cover default values or all possible enum values exhaustively.

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 performs RFM analysis on client data, scoring based on purchase behavior, segmenting into categories, and extracting ICP patterns. It specifies the verb 'run' and resource 'client data', but doesn't explicitly differentiate from sibling tools like 'qualify' or 'score_pipeline_health'.

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 through its explanation of what the tool does (analysis of purchase behavior for segmentation and pattern extraction), but doesn't provide explicit guidance on when to use this tool versus the sibling tools or any prerequisites. The context is clear but lacks alternative or exclusion statements.

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