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mentoring-inquiry-builder

by coach.marian

Start a mentoring inquiry with Marian Kamenistak — the 16-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 16 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
contextYesExplain 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."

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds that it returns specific data (discount, time promise, questions with ids, packages) but doesn't describe side effects or unusual behavior—which is appropriate given the safe, read-only profile.

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 description is compact (about 50 words), front-loads the key 'START HERE' signal, then lists the returned items and the follow-up. Every sentence contributes to usage and expectations, with no redundancy or filler.

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?

Given no output schema and a simple parameter set, the description enumerates all returned data (discount, time promise, material, questions, packages) and provides the next-step instruction. This is sufficient for an agent to know what to expect and how to proceed, though it could optionally mention the format of 'valid answer ids'.

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?

The single parameter 'context' is fully covered by the schema (100% coverage) with detailed instructions (word count, third-person, example). The description adds no extra parameter guidance, but the schema already carries the full burden, so a baseline of 3 is appropriate.

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 retrieves mentoring options (pricing, discount, questions, packages) for individuals and companies, using 'START HERE' to signal it as the entry point. It lists specific outputs and names the follow-up tool (match_mentoring_focus), distinguishing it from siblings without ambiguity.

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 explicitly says 'START HERE' for anyone considering mentoring, and instructs to call match_mentoring_focus after the visitor answers audience/role/motivation, giving a clear sequence. However, it doesn't mention when to use other siblings like book_intro_call or compose_mentoring_brief, leaving some comparison implicit.

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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TDQS

A4.4/5.0
Disambiguation5/5

Each tool maps to a distinct stage in the inquiry funnel: discovery, qualification, brief composition, offer delivery, and booking. The two booking tools are explicitly differentiated by buyer readiness, so there is no real ambiguity for an agent following the stated flow.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case, such as get_mentoring_options, match_mentoring_focus, compose_mentoring_brief, and send_mentoring_offer. This makes the set predictable and easy to navigate.

Tool Count5/5

Nine tools is well-scoped for a mentoring inquiry and booking pipeline. Each tool earns its place by covering a necessary step without excessive fragmentation or unnecessary duplication.

Completeness5/5

The tool set covers the full lifecycle from initial options discovery through qualification, program design, formal offer delivery, and booking confirmation. There are no obvious dead ends; even edge cases around undecided visitors or special deal terms are handled through the booking tools' branching logic.

Resources