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marvkr

Better Design

by marvkr
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TypeScript
Hybrid

Get Sales Principle

get-sales-principle
Read-onlyIdempotent

Load practical sales principles to handle objections, prepare champions, map features to value, and decide when honesty requires a different approach before live conversations or sales assets.

Instructions

Load practical sales guidance before a live conversation or before writing a sales asset.

Use this to handle objections, prepare a champion, map features to value, or decide when honesty means recommending a different approach. For objections, load the sales-principles topic and follow ACERS in order: Acknowledge, Clarify, Empathize, Reframe, Sell.

You can either:

  1. Request a specific topic or alias: get-sales-principle({ topic: "ACERS" })

  2. Search for the situation: get-sales-principle({ query: "help a champion answer an implementation objection" })

  3. Get the index of all sales principles: get-sales-principle({})

Use maxTokens to keep responses focused (recommended: 5000–10000).

Input Schema

NameRequiredDescriptionDefault
queryNoNatural language description of the sales conversation, objection, or asset.
topicNoSpecific sales topic or alias, e.g. sales-principles, ACERS, objection handling, champion enablement, or feature value.
contextNoOptional. One sentence on WHY you are calling this and what the user asked for (e.g. 'adding nav icons for the fintech dashboard'). Used only for usage analytics; does not change the result.
maxTokensNoMaximum tokens to return. Truncates content to fit. Recommended: 5000-10000.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already establish a safe, idempotent read. The description adds value beyond them by disclosing that maxTokens truncates content, that context is analytics-only and does not affect results, and that the no-argument call returns an index rather than content. Return structure beyond that is not described.

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?

Front-loaded with the purpose, then the when, then the three invocation modes — a sensible order. The numbered examples are slightly verbose relative to the schema text they restate, but nothing is 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?

For a read-only retrieval tool with no output schema, the description covers purpose, triggering situations, invocation modes, and truncation behavior. It leaves the shape of the returned guidance implicit and doesn't state what happens if a topic alias is unrecognized, which is the main remaining gap.

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 3 is the baseline, but the three enumerated calling patterns (topic+alias, natural-language query, no-arg index) add real operational meaning the schema alone does not convey. It also gives concrete alias examples and a recommended maxTokens band, though it does not explain precedence when both topic and query are supplied.

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 first sentence gives a specific verb+resource ('Load practical sales guidance') and the domain (sales) cleanly separates it from sibling principle guides like get-ux-principle and get-ui-principle. An agent can identify what this returns and when it applies without opening the schema.

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 names concrete triggering contexts ('before a live conversation', 'before writing a sales asset') and four jobs (objections, champion prep, feature-to-value mapping, honesty checks), plus an explicit ACERS procedure for objections. It stops short of naming when NOT to use it or which sibling to prefer for adjacent domains, so it misses the top band.

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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