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AIsa Apollo

Create Deal

post_apollo_opportunities
Destructive

Create a deal. Stage ids come from get_apollo_opportunity_stages, and the account it belongs to comes from post_apollo_accounts_search. Writes land in the AIsa workspace, which every caller shares: the record becomes visible and editable by others, and there is no per-caller isolation. Deals feed the workspace's forecast, so a test record distorts numbers other people read.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesDeal name
amountNoDeal amount
owner_idNoOwner ID
account_idNoAccount ID
closed_dateNoClosed date (date string)
typed_custom_fieldsNoTyped custom fields object
opportunity_stage_idNoDeal stage ID

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

The description adds significant behavioral context beyond the annotations: records land in a shared AIsa workspace, are visible/editable by all callers, have no per-caller isolation, and feed the workspace forecast so test records distort real numbers. This is exactly the kind of side-effect disclosure that annotations alone do not provide.

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 concise and effectively structured: one sentence states the operation, one gives ID sourcing guidance, and one gives critical shared-workspace side effects. Every sentence earns its place, and the most important caveat is front-loaded.

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 full schema coverage, an output schema, and rich behavioral disclosure, this is nearly complete for a create operation. It could add an explicit pointer to the update sibling for existing deals or to typed custom fields, but nothing that prevents an agent needs to invoke the tool correctly.

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?

The schema already describes all seven parameters, so the baseline is 3. The description goes beyond schema by explaining that `opportunity_stage_id` must come from `get_apollo_opportunity_stages` and `account_id` must come from `post_apollo_accounts_search`, adding meaningful provenance. The remaining parameters such as `owner_id`, `closed_date`, and `typed_custom_fields` receive no additional semantics beyond the schema.

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 opens with the concrete action and object, 'Create a deal,' and immediately ties the two key related parameters to their source endpoints, making it distinct from the get/patch opportunity siblings. The action, resource, and scope are immediately clear.

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

Usage Guidelines3/5

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

It provides useful where-to-get guidance: stage ids come from `get_apollo_opportunity_stages` and the account comes from `post_apollo_accounts_search`. It does not, however, explicitly state when to prefer this over patch/update alternatives, so usage boundaries are implied rather than fully spelled out.

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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