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OnStartups

Agent.ai MCP Server

by OnStartups

cold_call_prep_generate_call_game_plan

Generate a structured call game plan with pre-call intel, talk tracks, qualifying questions, objection playbook, and voicemail scripts to prepare for sales calls.

Instructions

Generates a structured Call Game Plan with pre-call intel, opening approach, talk tracks, qualifying questions, objection playbook (5 universal + prospect-specific), close, voicemail scripts, and delivery notes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
company_websiteYes
contact_nameYes
linkedin_urlNo
contact_roleNo
call_objectiveYescold_call
known_contextNoMutual connections, prior call outcomes, warm intro context.
seller_productYes
seller_icpNo
seller_websiteNo
pain_pointsNo
output_variable_nameYescall_game_plan
Behavior2/5

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

No annotations are provided, and the description does not disclose behavioral traits such as side effects (e.g., API calls, data persistence), required permissions, or assumptions about input quality. For a generative tool with 11 parameters, this omission is significant.

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

Conciseness3/5

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

The description is a single sentence that lists many components, which is moderately concise but could be better structured (e.g., bullet points) to improve scanability. It is front-loaded with the main purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 11 parameters, no output schema, and no annotations, the description is insufficient. It outlines output contents but does not describe how inputs map to outputs, potential limitations, or expected behavior for edge cases (e.g., missing contact_name).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema coverage is only 9% (one parameter described), yet the description adds no parameter-level explanation. Parameter names are self-explanatory, but the description does not clarify format, defaults, or relationships (e.g., how pain_points interacts with objection playbook).

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 generates a 'structured Call Game Plan' and enumerates 8 specific components (e.g., pre-call intel, opening approach, objection playbook). It uses a specific verb ('Generates') and resource, and distinguishes itself from sibling tools (no other call game plan tool exists).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives like outreach_drafter or meeting_prep. The description implies cold call preparation but does not specify contexts, prerequisites, or situations to avoid.

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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