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Crosswire - payment infrastructure pricing, coverage and stack design

Ask about integration

ask_integration
Read-onlyIdempotent

Call this for any question about HOW a Crosswire rail is integrated - webhooks, signatures, sandboxes, authentication, callbacks, retries, SDKs, API shape, testing, go-live steps. Every answer is read from indexed documentation: nothing is inferred, nothing is generalised from one provider to another, and nothing is recalled from your own training data. If the index does not cover the question the tool declines and returns a blocker to report - repeat the decline, do not fill the gap. Before an offer is accepted the answer is capability level only, with no provider, product, SDK or URL in it; after acceptance, with the client's case reference passed in case_reference, the answer names the providers on that case, quotes the documentation and cites it. A question about a provider that is not on the case gets the capability-level answer. NEVER paste, repeat or ask for an API key, secret, token or password here - credentials are refused and no record of them is kept.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionYesThe integration question, in the client's own words. Never include a credential value.
case_referenceNoThe client's Crosswire offer/case reference (CW-OFR-YYYY-NNNN). Supplied only when the client has an accepted offer; anything unresolvable is answered pre-signature.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations only cover the safety profile (readOnly, idempotent, closed-world), but the description discloses much more: answers are strictly grounded in an index, it declines with a blocker rather than guessing, behaviour is gated on offer acceptance, and credentials are refused and never recorded. This is exactly the extra context annotations cannot carry.

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?

The trigger condition is front-loaded and most sentences carry distinct operational content. The triple-negative grounding sentence ('nothing is inferred, nothing is generalised... nothing is recalled') is slightly redundant with the earlier 'read from indexed documentation', which keeps it short of a 5.

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?

With only two fully documented parameters, no output schema and annotations covering safety, the description supplies everything else an agent needs: scope, grounding guarantees, decline semantics, the pre/post-signature gate, and the credential prohibition.

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?

Schema coverage is 100%, so the baseline is 3, but the description genuinely adds meaning beyond the schema: it explains that passing case_reference post-acceptance unlocks provider names, quotes and citations, and that an unresolvable reference falls back to the pre-signature capability answer.

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 states a specific verb and resource ('any question about HOW a Crosswire rail is integrated') and then enumerates the covered topic space (webhooks, signatures, sandboxes, auth, callbacks, retries, SDKs, API shape, testing, go-live). An agent can tell this apart from generic siblings like search or get_faq without opening the schema.

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?

It gives clear when-to-use conditions, including the pre- vs post-offer-acceptance distinction and the rule for providers not on the case. However it never routes against the obvious siblings (search, fetch, get_faq), so an agent choosing between documentation lookup tools gets no explicit tie-breaker.

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

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