register_stats
Dashboard summary: provider counts, criticality distribution, ITS field completeness, exit plan and LEI coverage.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Dashboard summary: provider counts, criticality distribution, ITS field completeness, exit plan and LEI coverage.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It implies a read-only summary operation and lists the data categories, adding some context. However, it does not explicitly state that it is read-only, describe potential side effects, permissions, or output format.
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 a single concise phrase that front-loads the key term 'Dashboard summary' and enumerates the metrics. It is efficient and easy to parse, though it is a noun phrase rather than a complete sentence.
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 has no parameters and no output schema, the description provides a clear list of the summary contents, which is largely sufficient for an agent to know what to expect. It could add a note about return format, but the simplicity of the tool reduces the need.
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 an empty input schema. The baseline for 0 parameters is 4, and the description does not need to explain parameters. The schema coverage is 100%, so there is no gap.
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 resource as a dashboard summary and lists specific metrics it includes (provider counts, criticality distribution, ITS field completeness, exit plan, LEI coverage). It lacks an explicit verb but the intent is clear. It does not differentiate itself from sibling tools like list_providers or concentration_risk.
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 guidance on when to use this tool versus alternatives. No context, exclusions, or references to sibling tools are provided. The description simply states what the tool returns without any usage direction.
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.
Each tool targets a clear, distinct function: CRUD operations, analytics, validation, and export. There is no meaningful overlap between gap_analysis and validate_roi—one identifies data quality gaps while the other formally checks ITS compliance.
Most tools follow a verb_noun pattern (list_providers, get_provider, export_its, validate_roi), but a few use noun_noun or noun_verb forms (concentration_risk, gap_analysis, ctpp_check, health_check). The naming is readable and consistent in style (snake_case), but not uniformly verb-led.
The 10 tools are well-scoped for a DORA Register of Information domain, covering list/get/register, multiple analysis perspectives, validation, export, and health check. Each tool earns its place without redundancy.
The surface covers the core lifecycle (create, read, update via register_provider, list, export, validate) and adds useful analysis tools. The only notable gap is a delete_provider tool for removing deprecated or erroneous entries, but this is a minor omission.