List services
list_servicesThe seven services IG Digital Lab offers, each with a one-line summary and the canonical page URL. Use this to answer what the agency can build.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
list_servicesThe seven services IG Digital Lab offers, each with a one-line summary and the canonical page URL. Use this to answer what the agency can build.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are supplied, so the description carries the full burden. It usefully discloses the return shape (one-line summary plus canonical page URL per service), which compensates somewhat for the missing output schema, but says nothing about read-only nature, freshness, or any auth/rate constraints.
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 tight sentences with zero filler; the content of the result is front-loaded ahead of the usage hint. Every clause earns its place.
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?
With no input parameters, no annotations, and no output schema, the description covers what is needed: what the tool returns and when to reach for it. The only residual gap is the absence of any routing hint versus get_service_areas.
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 takes zero parameters, so there is nothing for the description to disambiguate. Baseline 4 applies for a parameterless tool.
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?
States a specific resource (the seven services the agency offers) and even quantifies the result set, plus what each entry contains. It does not explicitly differentiate itself from the sibling get_service_areas, which an agent could plausibly confuse with this tool.
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?
"Use this to answer what the agency can build" gives a clear positive usage context, so an agent knows when this is the right call. It stops short of naming exclusions or pointing to get_service_areas for the adjacent question, so no alternative routing is provided.
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.