One entry's manifest by slug. While no entries exist the honest answer is a not-found error carrying the E21 admission rule.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Entry slug (filename = @id slug, oh-validate-enforced). |
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 nature. The description adds meaningful behavioral context beyond annotations: missing entries produce a not-found error carrying the E21 admission rule. This is useful, though the E21 rule itself is unexplained and success behavior is not described.
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 short and front-loads the core function in the first sentence. The second sentence adds a specific error behavior without redundancy. The phrasing is slightly awkward ('While no entries exist') and 'E21 admission rule' is cryptic, but overall it is compact and efficient.
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?
For a one-parameter, read-only tool, the description is mostly adequate. However, there is no output schema and the description does not explain what a manifest contains or what the successful response looks like. Terms like 'manifest' and 'E21 admission rule' are domain-specific and left unexplained, which could hinder correct invocation.
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 slug parameter is already documented in the schema as 'Entry slug (filename = @id slug, oh-validate-enforced)'. The description adds little beyond confirming the manifest is accessed by slug, so it does not go beyond the schema baseline.
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 states the operation clearly: retrieve one entry's manifest by slug. It does not use an explicit verb, but the tool name 'manifest.get' plus 'by slug' conveys the action. It narrows scope with 'one entry', though it does not explicitly distinguish itself from sibling tools.
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?
There is no explicit guidance on when to use this tool versus alternatives. The description implies the caller should use it when they have a slug and want a manifest, but it names no sibling alternatives or exclusion conditions. The not-found behavior is mentioned, but not as usage 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.