Which EV Charger: the site's own MCP server — checker, enquiry (enquiry = a human handoff, not a...
Scored across 6 tools
The checker tools and enquiry tools form two clear groups, and within each group purposes are mostly distinct. One minor overlap exists: checker_answer returns the next question for a choice while checker_tree already contains the full decision graph, so an agent could use either to reason ahead.
The checker_ and enquiry_ prefixes make tool groups easily recognizable, and overall naming is readable. It is not perfectly uniform because checker_answer and checker_tree are noun-like while checker_start and submit_enquiry are verb-like, but the pattern is still predictable.
Six tools is well-scoped for this server: three cover the interactive decision guide and three cover the enquiry submission flow. Each tool serves a necessary role, and the count feels neither thin nor bloated.
The checker workflow is fully covered with start, answer, and full tree access, and the enquiry workflow is covered with descriptions, fields, and a two-step submission process. There are no obvious missing operations for the apparent scope of the server.
Given a question id and the chosen option (its choice index), return the next question or the final verdict.
| Name | Required | Description | Default |
|---|---|---|---|
| choice | Yes | ||
| question | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It does disclose the key behavior—returning either the next question or a final verdict—but it does not mention whether the flow state is mutated, what happens for invalid choices, or any session/state requirements.
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?
A single, information-dense sentence. The title and description work together without repetition or filler, and the key input/output behavior 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?
Adequate for a two-parameter tool: it names both inputs and describes the possible return. However, with no output schema and no annotations, it falls short of fully describing the response shape, error behavior, or what the caller should do with the returned next question/final verdict.
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 schema has 0% description coverage, so the description's clarification that `question` is a question id and `choice` is the chosen option's index is essential. It adds meaning beyond the raw property names and types, though it omits details like how to obtain valid question ids or bounds beyond minimum 0.
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 operation: given a question id and a choice index, return the next question or final verdict. This clearly differentiates it from sibling tools like checker_start or checker_tree, which have different roles in the flow.
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?
Usage is implied: use this when a user has answered a question and the flow should advance. However, it does not explicitly state when not to use it, what prerequisites exist (e.g., starting with checker_start), or how it relates to alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
The first question of the EV charger checker decision guide.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not state what invoking the tool does—whether it starts a session, presents a question, advances state, or returns data. The noun-phrase description leaves the actual behavior largely implied.
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 sentence with no filler and it front-loads the essential role of the tool. It earns its place, though it is too sparse to provide deeper context.
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 output schema and no annotations, the description should explain what the agent will receive and how to proceed. It only says 'first question' without clarifying the response format or the next step, so an agent has incomplete guidance for using this tool effectively.
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 for the description to carry. Nothing is missing 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 identifies a specific resource—the EV charger checker decision guide—and states that this tool is the first question, making it clear this is the entry point. It does not use an explicit action verb like 'starts' or 'initiates', but the title 'Start' and the phrase 'first question' make the purpose reasonably clear. It also implicitly distinguishes itself from answer/tree siblings.
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?
Usage is implied: call this tool first when beginning the EV charger checker decision guide. However, there is no explicit guidance about when not to use it, no mention of alternatives, and no indication of how it connects to checker_answer or checker_tree.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Every question, option and verdict of the EV charger checker guide, for reasoning end to end.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral disclosure burden. It conveys that the tool exposes static guide content, implying a read-only operation, but does not describe output shape, size, or whether the entire tree is returned at once. This is acceptable but not detailed.
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, well-structured sentence that communicates scope and intended use without filler. It is front-loaded with the key information that this is the complete decision tree.
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 parameterless tool, the description is reasonably complete: it states the content scope and the reasoning purpose. It does not explain the output format, and there is no output schema, but the 'decision tree' concept sufficiently implies a structured representation.
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, so there is no parameter semantics burden. A baseline of 4 is appropriate because there is nothing for the description to clarify about inputs.
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 tool's resource: the complete EV charger checker decision tree, including every question, option, and verdict. It distinguishes itself from siblings like checker_answer and checker_start by emphasizing the 'whole' tree, though it lacks an explicit verb like 'retrieve' or 'return'.
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?
'For reasoning end to end' provides a clear context for when to use the tool: when an agent needs the full guide rather than a single step/answer. It does not explicitly mention alternatives or exclusions, but the purpose is evident enough from the wording.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Read first. States plainly what submit_enquiry does on Which EV Charger: it starts an enquiry with human providers who quote directly. Nothing is bought, ordered or paid; no quote is guaranteed; it is free. Also returns who receives the details, the consent wording, and how the person confirms.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, and it does disclose key behavioral facts: nothing is bought, ordered, or paid; no quote is guaranteed; it is free; and it returns who receives details, the consent wording, and confirmation method. It does not explicitly state that enquiry_describe itself is read-only or side-effect free, but the descriptive framing implies it.
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 front-loaded with 'Read first' and every sentence adds useful content about the enquiry's behavior or return value. It is slightly redundant with the title's mention of 'not a purchase, not a guaranteed quote,' but overall it is compact and well-ordered.
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 zero-parameter informational tool with no output schema, the description is quite complete: it states what the related submit_enquiry does, what it does not do, and what this tool returns. It could be more precise about the exact return format, but that is a minor gap for a descriptive tool.
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 the schema description coverage is 100%, so the baseline is 4. The description adds no parameter-specific information, but none is needed because there are no parameters to explain.
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 identifies a specific verb and resource: it 'states plainly what submit_enquiry does on Which EV Charger,' and clarifies the expected outcome (an enquiry, not a purchase or guaranteed quote). It does not explicitly differentiate itself from sibling tools like submit_enquiry or enquiry_fields, so it falls short of a 5, but the purpose is clear and non-tautological.
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?
'Read first' is an explicit directive to use this tool before proceeding with submit_enquiry, and the description explains what to expect from that submission. It gives clear context but does not spell out when not to use this tool or name alternatives, so it lacks the full exclusionary guidance needed for a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Every field of the Which EV Charger enquiry: key, label, type, whether required, help text and the allowed options where there are any. Pass answers to submit_enquiry keyed by field key.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral burden. It discloses the complete set of returned attributes and notes that options are included only where they exist. The read-only nature is implied by the content and phrasing, though not explicitly stated; this is a minor gap.
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 no filler. The first sentence front-loads the exact content of the response, and the second sentence gives a clear downstream use. Every word 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?
For a parameterless introspection tool, the description is complete: it names the enquiry, lists all field metadata returned, and explains how to use the field keys with submit_enquiry. No output schema or annotations are present, but the description covers what an agent needs to know to call and consume this tool.
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, so parameter semantics are trivially satisfied and the baseline is 4. The description adds value by explaining how the output keys relate to submit_enquiry, which is more than an empty schema requires.
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 — 'Every field of the Which EV Charger enquiry' — and enumerates exactly what is exposed: key, label, type, required, help text, and options. It lacks an explicit action verb like 'retrieves' or 'lists', and it does not differentiate itself from siblings such as enquiry_describe, so it stops short of a 5.
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 provides practical usage context: 'Pass answers to submit_enquiry keyed by field key.' This tells an agent why it would call this tool and how the result feeds another tool. It does not explicitly address when not to use it or contrast it with sibling tools, so the guidance is useful but not exhaustive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Submits an enquiry to Which EV Charger — NOT a purchase, NOT a guaranteed quote. Step 1: call with the answers (keyed by field key from enquiry_fields) and consent=true; it validates and returns a summary, the consent line and a confirmation token — show the person the summary and the consent line. Step 2: only if the person agrees, call again with the same answers, consent=true and the confirmation token; the enquiry is then submitted, and the person receives an email with a link they must click before any provider sees it. Consent means the person has read and agreed to: "Happy for my details to go to local EV charger installers, who'll contact me directly."
| Name | Required | Description | Default |
|---|---|---|---|
| answers | Yes | the person's answers, keyed by field key | |
| consent | Yes | true only when the person has agreed to: Happy for my details to go to local EV charger installers, who'll contact me directly. | |
| confirmation | No | the confirmation token from step 1, after the person has approved the summary |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the full disclosure burden and meets it: it explains validation before submission, the returned summary/consent/token, the required consent line, and the post-submission email-link requirement. It also clarifies that no provider sees the enquiry until the person clicks the link.
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 longer than average but every sentence earns its place: the non-purchase disclaimer is front-loaded, and the two steps are clearly numbered. The consent line is repeated verbatim, which removes ambiguity about what consent means.
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 consent-sensitive two-step submission with no annotations and no output schema, this description gives enough guidance to call the tool correctly end-to-end. It covers prerequisites, the two call phases, the consent text, and the delivery/visibility outcome; missing error-handling details are not essential for 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?
The schema already describes all three parameters (100% coverage), so the baseline is 3; the description adds useful sequencing by tying 'confirmation' to the step-1 return value and 'answers' to enquiry_fields. It does not exhaustively redefine the parameter types, but it gives the agent the workflow context needed to populate them correctly.
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 names a specific action ('submits an enquiry') and a specific target ('Which EV Charger', human providers), and explicitly disambiguates from a purchase or guaranteed quote. This separates it from the sibling enquiry_describe/enquiry_fields tools by outcome, so an agent knows what this tool is for.
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?
It provides a precise two-step invocation protocol, states the condition for proceeding to step 2 ('only if the person agrees'), and gives a when-not boundary ('NOT a purchase, NOT a guaranteed quote'). It also points to enquiry_fields as the source of answer keys, giving the agent the surrounding workflow context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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