List the position statements and result reports of one consultation IRI: use after get_consultations to read the genesis record. norm.
| Name | Required | Description | Default |
|---|---|---|---|
| consultation | Yes | The consultation IRI (from get_consultations). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already establishes the read-only safety profile, and the description adds a little context by framing this as reading the 'genesis record.' However, it does not disclose return shape, empty-result behavior, or error handling, so the added behavioral transparency is limited.
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 main instruction is front-loaded and compact, but the trailing 'norm.' appears to be unexplained noise, and 'genesis record' is vague. This prevents the description from being as clean and purposeful as it could be.
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 single required parameter, complete schema coverage, and readOnlyHint annotation, the description provides enough context for a simple list operation. It identifies the input source, the output category, and the workflow position, though an output schema or a bit more detail on results would make it fully complete.
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 coverage is 100% and the parameter description already says 'The consultation IRI (from get_consultations).' The tool description reinforces 'one consultation IRI' but does not add meaningful new detail beyond the 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 clearly identifies the action ('List') and the resource ('position statements and result reports of one consultation IRI'). It also distinguishes this from the related get_consultations flow by specifying that it operates on a single consultation IRI.
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 says 'use after get_consultations', giving the agent a clear workflow trigger. It does not name alternatives or state when not to use the tool, so it falls just short of full guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The tools are strongly namespaced and most have a clear 'use for' hint, so an agent can usually select correctly. A few near-neighbour pairs, such as fedlex.get_citations vs fedlex.get_references and facts.badge vs facts.latest, require careful reading but are still distinguishable.
The <domain>.<snake_case_action> style is consistent and the fedlex/lindas families are predictable. However, several noun-style names such as meta.tools, lindas.observations, and facts.badge deviate from the verb_noun pattern, and the variety of get_/read_/list_/find_ verbs adds minor noise.
With 52 tools, this is a very large MCP surface for one server; while each tool appears individually purposeful, the combined set is heavy for an agent to explore and select from. The gateway would be more manageable split into separate legal, data, and meta servers.
The Fedlex cluster covers the full legal-research workflow: search, version resolution, reading, comparison, citation checking, history tracing, consultations, and official publications. The LINDAS cluster covers cube discovery, schema inspection, filtering, and label resolution, and the directory/meta tools complete the capability-discovery loop. There are no obvious dead ends or critical missing operations.