Skip to main content
Glama

ppl - Personal CRM for AI Agents

Update Call

calls.update

When a logged call's details need correcting.

Input Schema

NameRequiredDescriptionDefault
call_idYesThe call id.
contentNoOptional notes about the call.
called_atYesDate of the call (any parseable date).
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

C2.7/5.0
Behavior2/5

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

Annotations already declare readOnly=false, idempotent=false, destructive=false, and closed-world, so the safety profile is covered by structured data. The description adds nothing beyond that — it does not mention the approval_id single-use requirement, whether the update is reversible, or what happens to unspecified fields.

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?

It is a single short sentence fragment with zero waste, but it is under-specified rather than genuinely concise — brevity here comes at the cost of substance rather than from tight editing of a complete thought.

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?

For a five-parameter mutation tool that consumes a single-use human approval ID, the description is thin: it omits prerequisites, scope of change, and confirmation of behavior. An output schema and rich annotations carry some load, but the agent still lacks enough to call this confidently.

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 including the nuanced approval_id and called_at are documented in the schema itself. The description mentions no parameters at all, so it neither compensates nor detracts; baseline 3 applies.

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

Purpose3/5

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

The name and title say 'Update Call', and the description frames the purpose as correcting a logged call's details, so the verb+resource is recoverable. However, the description itself never says it updates an existing call record nor which fields it can change, and it does nothing to distinguish this from calls.create, calls.get, or calls.delete.

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 gives an implied trigger ('when details need correcting'), which is a usable usage cue. But it names no alternatives, no when-not conditions, and no prerequisites such as the call needing to already be logged — an agent must infer the rest from the sibling list.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.