yesmcp

Scenario playbook for a business type

advise_scenarios

Read-onlyIdempotent

Given a business type in the user's own words (for example hair salon, restaurant, dental clinic), returns yesmcp's curated playbook: what that business's customers could do inside AI chats, what the business's own team could run from their chat, what building it takes, and a concrete next step. When no playbook exists for the exact business type, the tool returns the closest one — say clearly that it is adjacent guidance and do NOT invent specifics for the business type the user named. Called without answers, the tool also returns two short intake questions: ask them as they are written, then call the tool again with the user's answers to get the scenario map with a feasibility verdict.

Input Schema

TableJSON Schema

Name	Required	Description
`focus`	No	Which half of the scenario map to show. Defaults to `both`; pass `customers` or `team` only when the user asked for one of them specifically.
`answers`	No	The user's answers to the intake questions this tool returns when called without them. Any subset is accepted; pass only what the user actually said.
`businessType`	Yes	The user's business type, in their own words.

Output Schema

TableJSON Schema

Name	Required	Description
`focus`	Yes	Which shelves were asked for.
`shelves`	Yes	Playbook bullets, verbatim; the shelf the focus filtered out is empty.
`nextStep`	Yes	The playbook's own next step, or null.
`vertical`	Yes	The matched playbook's human title, or null.
`channelNote`	Yes	Derived only from `answers.customer_channel`; null when that answer was not given.
`feasibility`	Yes	Derived only from `answers.systems`; null when that answer was not given.
`matchedStatus`	Yes	`adjacent` means the map is the closest playbook, not this vertical's own.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedSep 6, 2026

TDQS

A4.7/5.0

Behavior5/5

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

The description discloses important behavior beyond the readOnly and idempotent annotations: it returns the closest playbook when an exact match is absent, explicitly instructs the agent to label that as adjacent guidance and not invent specifics, and describes the intake-question flow. This is exactly the kind of non-obvious behavior an agent needs to know before calling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but every clause earns its place: purpose, playbook contents, fallback rule, no-invention guardrail, and the two-step intake workflow. It front-loads the core action and keeps all critical usage constraints in one coherent block.

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?

The tool's complexity is well covered: the description explains the scenario, the fallback, the intake flow, and how to handle partial answers. The output schema exists to explain return values, so the description does not need to redundantly describe them. Nothing essential is missing for correct invocation.

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 adds meaningful parameter context: `businessType` should be in the user's own words, `answers` is the response to previously returned intake questions, and any subset of answers is acceptable. This goes beyond the schema by explaining the intended calling pattern.

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 ('returns yesmcp's curated playbook') for a business type, and immediately clarifies what the playbook contains. It also distinguishes the tool from the booking-oriented sibling tools by focusing on scenario guidance rather than scheduling or service listing.

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?

The description gives clear workflow guidance: call without `answers` to get intake questions, then call again with answers. It also explains fallback behavior when no exact playbook exists. It does not explicitly name alternative sibling tools, but the context is clear enough that an agent would not confuse this with a booking tool.

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

A4.3/5.0

Disambiguation4/5

Most tools are clearly distinct: booking lifecycle (book, cancel, reschedule, availability), services, scenarios, and meta tools each target different actions. The widget/non-widget pairs (book_consult vs booking_widget, get_services vs services_widget) and list_availability vs booking_widget could cause confusion, but the descriptions explicitly state which to prefer and when.

Naming Consistency3/5

Most tools follow verb_noun (book_consult, cancel_booking, reschedule_booking, get_services, list_availability, advise_scenarios), but four break the pattern with noun_noun or gerund forms (booking_widget, services_widget, directory_census, demo_walkthrough). The mix is readable but inconsistent, especially the widget pairings that differ from their non-widget counterparts.

Tool Count5/5

Ten tools is well-scoped for a consultation and advisory service server. Each tool earns its place: full booking lifecycle, services catalog, scenario playbooks, and reviewer-facing meta tools. No redundant or filler tools.

Completeness4/5

The booking lifecycle is fully covered (list, book, cancel, reschedule) plus interactive widgets, and services/scenario discovery is solid. The only notable gap is that cancel/reschedule require the email confirmation reference — there is no 'list my bookings' tool to look up bookings by email. The demo/census tools are meta but deliberately scoped.

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