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ppl - Personal CRM for AI Agents

Create Call

calls.create

When the user tells you about a phone call that happened, like "I just called Mom". Logs it with the date, notes, and who called whom.

Input Schema

NameRequiredDescriptionDefault
contentNoOptional notes about the call.
called_atYesDate of the call (any parseable date).
contact_idYesThe contact's API id.
approval_idNoID of a human-approved exact tool request from this credential. Single use on successful execution.
contact_calledNoWhether the contact was the one who called.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare this is a non-readonly, non-idempotent, non-destructive write, so the safety profile is covered. The description adds that it records date, notes, and caller direction, but says nothing about the approval_id parameter's human-approval workflow, which is the most notable behavioral trait of this tool.

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?

Two short sentences with the usage trigger front-loaded and an inline example that grounds the intent. No filler, though the example interrupts the flow slightly rather than following the action statement.

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

Completeness3/5

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

Output schema exists, so return values need not be described, and the trigger plus recorded fields cover the core use. Still missing are the approval_id workflow context and any routing guidance against the many logging siblings, which a write tool in this dense toolset should provide.

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?

Schema description coverage is 100%, so all five parameters are already documented in the schema. The description's 'date, notes, and who called whom' maps onto called_at, content, and contact_called but adds no format detail or meaning beyond the schema, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Logs') and resource (a phone call) with the fields recorded, which is clear enough to distinguish it from a generic note or journal entry. It does not explicitly differentiate from siblings like interactions.log or calls.update, but the verb+resource combination is unambiguous.

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?

Gives a usable trigger ('when the user tells you about a phone call that happened') with a concrete example, so the agent knows the context. However, it offers no exclusions and never mentions the closely related interactions.log, so an agent cannot tell whether a call should be logged here or there.

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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