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SalesHookAI

Find customer

fetchCustomerContext
Read-onlyIdempotent

Finds a customer by name, company or e-mail (query) and returns the best match with contact data. Returns nothing found if no customer matches.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "fetchCustomerContext"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesName, company or e-mail of the customer to find.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare a safe, read-only, idempotent, closed-world lookup, so the safety profile is fully covered. The description adds two genuinely useful behaviors: it returns only the single best match (not a list) and reports nothing found when there is no match. However, with no output schema, 'contact data' is too vague to tell the agent what fields come back.

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?

Two tight sentences, front-loaded with the lookup, followed by the not-found behavior. Slightly awkward phrasing in the second sentence ('Returns nothing found'), but no filler and nothing to cut.

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

Completeness4/5

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

For a one-parameter read-only lookup with rich annotations and full schema coverage, the description covers the essential call contract. The remaining gap is the return payload shape and multi-match behavior, minor for a 'best match' finder but not negligible without an output schema.

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 single parameter already documents that it accepts a name, company or e-mail. The description restates '(query)' and the same accepted values without adding format hints (e.g. partial vs exact match, precedence when a string could be both a name and an e-mail), so it only matches the schema baseline.

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

Purpose4/5

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

States a specific verb and resource (find a customer) plus the searchable fields and result semantics ('best match with contact data'). It is clear enough to separate from saveCustomer/updateCustomer, but it never distinguishes itself from single-customer siblings like fetchCustomerDetailContext, leaving the 'which fetch tool' question partly open.

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

Usage Guidelines3/5

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

Usage is implied: call this to locate a customer when you have a name, company or e-mail. There is no explicit when-not guidance or routing to alternatives such as fetchCustomerDetailContext for full detail, so the agent must infer the boundary itself.

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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