get_coveragePer-source coverage and freshness. Call this first when unsure whether Lexiara holds the law you need — absence of coverage means 'not here', never 'does not exist'.
| Name | Required | Description | Default |
|---|---|---|---|
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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?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description goes beyond annotations by disclosing the key behavioral nuance: absence of coverage means 'not here' rather than 'does not exist' — crucial context for interpreting results. This adds genuine value beyond the annotation layer.
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?
Two sentences with zero waste. The first sentence states the function, the second provides use timing and result interpretation — each clause earns its place. High-value information is front-loaded.
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 zero parameters, no output schema, and annotations covering safety, the description provides sufficient guidance for correct invocation: what the tool returns (coverage and freshness), when to call it, and how to avoid misinterpreting the absence of coverage. Slightly more detail on return format would be nice, but the tool's simplicity makes this largely 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?
The tool has zero parameters and schema description coverage is 100%, so there is no parameter documentation burden. The description correctly focuses on output semantics instead. Baseline 4 for zero-parameter tools is appropriate here.
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 a specific verb and resource: 'Per-source coverage and freshness.' It clearly distinguishes this tool from siblings by positioning it as the first call when unsure whether Lexiara holds the needed law, and the title reinforces the purpose. The 'not here vs does not exist' clarification adds important semantic 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 gives explicit guidance on when to call this tool ('Call this first when unsure whether Lexiara holds the law you need') and how to interpret results. However, it does not name specific sibling tools or explicitly state when not to use alternatives, which prevents a 5.
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.
Most tools have clearly distinct purposes, and descriptions carefully separate overlapping areas such as definition lookup, cross-references, and transposition links. A few citation/graph tools (related_works, work_mentions, find_national_implementations, provision_context) could be confused at a glance, but their granularity and direction are explicitly differentiated.
Naming follows a readable all-lowercase-snake_case style, but conventions are mixed: roughly half are imperative verb_object names (lookup_provision, search_legislation, list_topics) while the rest are bare noun-phrase view names (provision_context, recent_changes, work_mentions). The pattern is understandable but not uniform.
At 18 tools, the set is slightly above the ideal 3-15 range, but each tool maps to a distinct research query or data product. The count is justified by the breadth of legal-research operations rather than redundancy.
The surface covers the domain thoroughly: search, provision lookup, definitions, multilingual terms, cross-references, amendment history, transposition links, topics, coverage, updates, and review workflows. The explicit read-only design means absent write operations are a deliberate boundary, not a gap.