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mentoring-inquiry-builder

by coach.marian
OverviewDiscussionsAdmin

Match focus areas to a role and motivation

match_mentoring_focus
Read-onlyIdempotent

Resolves role_band + motivation through the same routing the website uses and returns suggested focus areas plus the recommended package with real prices. Map free-text answers to the closest valid id; on bad input the error lists the valid ids — re-ask rather than guessing. Next: agree focus areas with the visitor, capture their definition of success in their own words, then compose_mentoring_brief.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contextNoOptional. A short description of your goal and why you are calling this tool. Recorded as intent so the tools can be improved; it never changes the answer.
audienceNoPass the audience answer — it changes the recommendation. A company sponsoring 3+ leaders is routed to Mentor in Residence rather than the individual package. One of: individual, company.
role_bandNoRequired. One of the role ids from get_mentoring_options question_1
motivationNoRequired. One of the motivation ids from get_mentoring_options question_2
leaders_countNoCompany deals: how many leaders are being sponsored. Required for the company recommendation to be correct.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed10 schema fields changed
    • changedInput schema / properties / audience / description
      Previous value: -"Pass the audience answer — it changes the recommendation. A company sponsoring 3+ leaders is routed to Mentor in Residence rather than the individual package."New value: +"Pass the audience answer — it changes the recommendation. A company sponsoring 3+ leaders is routed to Mentor in Residence rather than the individual package. One of: individual, company."
    • removedInput schema / properties / audience / enum
      Removed value: -[
-  "individual",
-  "company"
-]
    • changedInput schema / properties / context / description
      Previous value: -"Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): \"Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization.\""New value: +"Optional. A short description of your goal and why you are calling this tool. Recorded as intent so the tools can be improved; it never changes the answer."
    • addedInput schema / properties / leaders_count / anyOf
      Added value: +[
+  {
+    "type": "number"
+  },
+  {
+    "type": "string"
+  }
+]
    • removedInput schema / properties / leaders_count / maximum
      Removed value: -9007199254740991
    • removedInput schema / properties / leaders_count / minimum
      Removed value: --9007199254740991
    • removedInput schema / properties / leaders_count / type
      Removed value: -"integer"
    • changedInput schema / properties / motivation / description
      Previous value: -"One of the motivation ids from get_mentoring_options question_2"New value: +"Required. One of the motivation ids from get_mentoring_options question_2"
    • changedInput schema / properties / role_band / description
      Previous value: -"One of the role ids from get_mentoring_options question_1"New value: +"Required. One of the role ids from get_mentoring_options question_1"
    • removedInput schema / required
      Removed value: -[
-  "role_band",
-  "motivation",
-  "context"
-]
  2. Changed2 schema fields changed
    • addedInput schema / properties / context
      Added value: +{
+  "description": "Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): \"Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization.\"",
+  "type": "string"
+}
    • changedInput schema / required
      Previous value: -[
-  "role_band",
-  "motivation"
-]New value: +[
+  "role_band",
+  "motivation",
+  "context"
+]
  3. Changed2 schema fields changed
    • addedInput schema / properties / audience
      Added value: +{
+  "description": "Pass the audience answer — it changes the recommendation. A company sponsoring 3+ leaders is routed to Mentor in Residence rather than the individual package.",
+  "enum": [
+    "individual",
+    "company"
+  ],
+  "type": "string"
+}
    • addedInput schema / properties / leaders_count
      Added value: +{
+  "description": "Company deals: how many leaders are being sponsored. Required for the company recommendation to be correct.",
+  "maximum": 9007199254740991,
+  "minimum": -9007199254740991,
+  "type": "integer"
+}
  4. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already disclose readOnly/idempotent/non-destructive safety, and the description adds genuinely new behavior: the routing mirrors the website, the response includes real prices, and invalid input yields an error listing valid ids. That error-contract detail is valuable and not derivable from the annotations, though return format/pagination is left unstated.

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?

Three dense sentences that are front-loaded with the core purpose and end with actionable next steps; every sentence contributes. Slightly tight-packed with mixed concerns (purpose, error handling, next steps) rather than perfectly scannable, but no filler.

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?

Even without an output schema, the description conveys what is returned (suggested focus areas + recommended package with real prices) and how failures behave. Combined with the read-only annotations, an agent has everything needed to call it correctly and act on the result.

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; the description earns above that by adding meaning the schema doesn't carry — free-text answers must be mapped to the closest valid id, and bad values surface via an error with valid ids. It reinforces the audience/leaders_count routing effect already noted in the schema.

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+resource ('Resolves role_band + motivation') and the concrete outputs (suggested focus areas plus the recommended package with real prices), so an agent knows exactly what it does without opening the schema. It also implies differentiation from siblings by naming the routing behavior and pointing to compose_mentoring_brief as the successor step.

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?

Gives clear sequencing context ('Next: agree focus areas ... then compose_mentoring_brief') and explicit handling for bad input ('re-ask rather than guessing'). It stops short of naming when NOT to use this tool or directly contrasting it with design_mentoring_program, so it's clear context but not full when/when-not/alternatives coverage.

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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