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Bat Survey Cost: the site's own MCP server — enquiry (enquiry = a human handoff, not a...

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Status
Healthy
Uptime
100.0% over 39 days
Last Tested
Transport
Streamable HTTP · MCP 2025-11-25
URL

TDQS

A4.4/5.0

Scored across 3 tools

Disambiguation5/5

Each tool has a clearly distinct role: enquiry_describe explains the process/consent, enquiry_fields returns the input schema, and submit_enquiry performs the submission. There is no overlap in purpose or resource targeting, so an agent can select correctly with confidence.

Naming Consistency4/5

All names use snake_case and share the 'enquiry' token, which keeps them grouped and readable. However, the ordering is inconsistent: enquiry_describe/enquiry_fields use noun_verb while submit_enquiry uses verb_noun.

Tool Count4/5

Three tools is on the thin side, but each maps to a necessary step of a single-purpose enquiry flow (understand, get fields, submit). Nothing is redundant, though there is little surface beyond this one workflow.

Completeness4/5

The set covers the full enquiry lifecycle including consent disclosure, field schema, and a two-step submit with confirmation token. Minor gaps exist (no status/retrieval of a submitted enquiry), but the email-link flow implies that is handled outside the tool surface.

Available Tools

3 tools
enquiry_describeWhat you get: an ENQUIRY with a human (not a purchase, not a guaranteed quote)AInspect

Read first. States plainly what submit_enquiry does on Bat Survey Cost: 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.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden of disclosing behavior. It transparently explains what submit_enquiry does (starts an enquiry, nothing is bought/guaranteed, free) and what enquiry_describe itself returns. It does not explicitly state that enquiry_describe has no side effects, but 'Read first' and 'States plainly' strongly suggest a read-only explanatory operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured: it front-loads the key instruction ('Read first'), states the core purpose, clarifies what is NOT true about the enquiry, and then lists the return content. Every sentence adds value and there is no redundancies.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter, no-output-schema explainer tool, the description is complete. It covers what the tool does, why an agent should read it first, what submit_enquiry does and does not do, and what information the describe tool returns. Nothing essential is missing for selecting and invoking this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so there are no parameter semantics to explain. The description still provides useful context about what the tool does, but it does not need to add parameter-level detail because the input schema is empty and coverage is 100%.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's role: it 'States plainly what submit_enquiry does on Bat Survey Cost' — a descriptive, meta-level action distinct from performing the enquiry. The verb 'states' plus the resource 'what submit_enquiry does' makes the purpose specific and differentiates it from the sibling action tool submit_enquiry.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The opening phrase 'Read first' gives a clear directive to use this tool before engaging with submit_enquiry. It does not explicitly name alternatives or exclusions, but the context strongly implies this is the preparatory/explainer tool, so an agent can infer when to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

enquiry_fieldsThe questions the enquiry asksAInspect

Every field of the Bat Survey Cost 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.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral burden. It discloses the exact content of the result and implicitly indicates this is a read-only metadata operation by telling the agent to pass answers elsewhere. It could be more explicit about having no side effects, but the behavior is strongly implied.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences deliver the essential information without redundancy. The content is front-loaded and every sentence contributes meaning, including the cross-reference to submit_enquiry.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Since there is no output schema, the description fully accounts for what the returned data will contain. It names all relevant field metadata and provides the key relationship to submit_enquiry, making the tool self-sufficient for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so there is nothing to clarify. The description instead adds meaning to the output fields by naming their attributes and explaining how the field key should be used with submit_enquiry.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description specifies exactly what the tool exposes: every field of the Bat Survey Cost enquiry with key, label, type, required flag, help text, and allowed options. This clearly separates it from submit_enquiry, since it is about inspecting fields rather than submitting answers.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The sentence 'Pass answers to submit_enquiry keyed by field key' gives practical usage guidance and connects this tool to the submission sibling. It does not explicitly contrast with enquiry_describe, but the context is clear enough that an agent knows this tool is for field metadata.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

submit_enquirySubmit an ENQUIRY to human providers (two steps; not a purchase)AInspect

Submits an enquiry to Bat Survey Cost — 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: "Send my contact details to up to three relevant ecologists, chosen by Bat Survey Cost, who'll contact me directly. I'll be emailed each firm's name as my details go to it, and can stop any more firms getting them."

ParametersJSON Schema
NameRequiredDescriptionDefault
answersYesthe person's answers, keyed by field key
consentYestrue only when the person has agreed to: Send my contact details to up to three relevant ecologists, chosen by Bat Survey Cost, who'll contact me directly. I'll be emailed each firm's name as my details go to it, and can stop any more firms getting them.
confirmationNothe confirmation token from step 1, after the person has approved the summary

TDQS

A4.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden well: it discloses validation behavior, the returned summary/consent line/token, the confirmation-email click gate, and that contact details go to up to three ecologists who contact the person directly. It omits failure modes (invalid/expired token, consent=false) and rate/volume limits, so not quite full disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the most important caveat before the mechanics, and the step-by-step sequencing is easy to scan. Slightly over-long due to the inline consent quote, which is already reproduced in the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, and the description compensates by naming what each step returns (summary, consent line, confirmation token). For a nested-object, two-phase mutation with no annotations, this covers everything an agent needs to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the consent text is duplicated verbatim from the schema, so most parameter meaning is already structured. The description adds only the ordering relationship (answers keyed by enquiry_fields; confirmation token comes from step 1), which is largely restated within the schema descriptions themselves.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Submits an enquiry to Bat Survey Cost") and immediately bounds it with "NOT a purchase, NOT a guaranteed quote." It also references the sibling enquiry_fields as the source of the answer keys, so an agent can tell it apart from the descriptive siblings without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit two-step protocol: Step 1 with answers + consent=true to validate and obtain a token, Step 2 only if the person agrees. It names the condition that selects each call and the gate (person approval, email click) before providers see anything.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool update
    • Changedsubmit_enquiry1 field changed
      • changedInput schema / properties / consent / description
        Previous value: -"true only when the person has agreed to: Happy for my details to go to relevant licensed ecologists, who'll quote me directly."New value: +"true only when the person has agreed to: Send my contact details to up to three relevant ecologists, chosen by Bat Survey Cost, who'll contact me directly. I'll be emailed each firm's name as my details go to it, and can stop any more firms getting them."
  2. 3 tool updates
    • First observedenquiry_describe
    • First observedenquiry_fields
    • First observedsubmit_enquiry

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