get_eta_i_metric
Read the public platform intelligence-efficiency metric. Free. [free]
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| days | No |
Read the public platform intelligence-efficiency metric. Free. [free]
| Name | Required | Description | Default |
|---|---|---|---|
| days | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the metric is public and free, and that the operation is a read, but it does not mention return format, any potential limitations, or behavior beyond the basic read. This is insufficient for full transparency.
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 very brief, which is appropriate for a simple tool, but it contains redundancy: 'Free. [free]' repeats the same information. It is front-loaded with the main verb and resource, but the extra phrase adds little value.
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 parameter 'days' is unexplained, and there is no output schema, the description leaves the agent without enough context to correctly use the tool. It does not specify how the 'days' parameter affects results or what the metric represents beyond the name.
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 input schema has one parameter 'days' with no description (schema description coverage is 0%). The description provides no explanation of what 'days' controls or its meaning. The description fails to compensate for the schema's lack of semantic information.
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 action ('Read') on a specific resource ('the public platform intelligence-efficiency metric'), which clearly distinguishes it from the list of sibling tools. The verb+resource structure is clear, though it does not explicitly name alternatives.
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?
No guidance is provided on when to use this tool versus its siblings. The phrase 'Free. [free]' hints at accessibility but offers no contextual or conditional usage information.
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.
Several tools overlap heavily: get_node_score vs get_energy_node_score, find_local_installers vs match_installers, and route_lead vs submit_contractor_match_request are easy to confuse. The descriptions clarify details, but an agent would often need to inspect arguments to know which installer, incentive, or recommendation tool is the right one.
All tool names use snake_case with a verb-leading style, which provides a consistent backbone. However, domain naming is inconsistent: the same concept appears as node vs energy_node, installer vs contractor, and incentive discovery is split across check_incentives, get_energy_incentives, list_guides, and get_guide without a predictable pattern.
29 tools is too many for a single MCP server, especially since several fall into overlapping installer/lead, incentive, recommendation, and commercial-power categories. Many tools appear to be monetization gates or handoff variants that could reasonably be consolidated.
The set covers core user journeys: assessment creation/answering/completion, incentive guidance, installer discovery and routing, quote review, and commercial power screens. However, there are notable gaps in state management, such as no way to list or retrieve existing assessments/leads, and several checkout or handoff tools have no follow-up/status tool.