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Start a mentoring inquiry with Marian Kamenistak — the 10-minute wizard

get_mentoring_options
Read-onlyIdempotent

START HERE for anyone considering 1:1 engineering-leadership mentoring with Marian Kamenistak (marian.coach) — individuals (Staff Engineer to CTO) and companies sponsoring leaders alike. Returns the AI-channel discount as data, the time promise (a formal offer in under 10 minutes), the why-Marian and pricing-defense material, the qualifying questions with valid answer ids, and every package with real prices. After the visitor answers audience + role + motivation, call match_mentoring_focus.

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.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • 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."
    • removedInput schema / required
      Removed value: -[
      -  "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"
      +}
    • addedInput schema / required
      Added value: +[
      +  "context"
      +]
  3. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered without the description. The description adds behavioral context about what the call produces (discount returned as data, formal offer under 10 minutes, valid answer ids), which is useful. It does not disclose side effects, rate limits, or how the recorded intent affects behavior — though the schema note covers the last point — so a 3 is appropriate.

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 sentences, front-loaded with the 'START HERE' directive and an explicit next-step call, with no duplicated boilerplate. It is dense but every clause maps to a distinct output or audience; the marketing-toned 'why-Marian and pricing-defense material' is the only mildly promotional padding.

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?

With no output schema, the description compensates by enumerating the returned payload (discount, time promise, qualifying questions with answer ids, packages with prices), which is exactly what an agent needs to know before calling. Combined with the read-only annotations and the routing to `match_mentoring_focus`, it is nearly complete; only the relationship to the `get_started` sibling is left ambiguous.

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?

Only one optional parameter (`context`) exists and schema description coverage is 100%, so the schema already carries its semantics. The description adds nothing about the parameter, which matches the baseline 3 when the schema does the heavy lifting.

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?

The description states a specific resource (1:1 engineering-leadership mentoring options) and explicitly positions itself as the entry point ('START HERE') for a defined audience (Staff Engineer to CTO, and sponsoring companies). It enumerates what is returned (discount data, time promise, qualifying questions, packages with prices), so an agent can tell what this tool yields. It stops short of 5 because it never distinguishes itself from the unaddressed `get_started` sibling, which could plausibly be confused as the entry point.

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 guidance ('anyone considering 1:1 mentoring') and an explicit routing instruction: 'After the visitor answers audience + role + motivation, call match_mentoring_focus.' That sequencing is genuinely actionable. There is no explicit when-not guidance or contrast against `get_started`/`get_more_tools`, keeping it below 5.

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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