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Gong

by io.github.pipeworx-io

Gong List Calls

gong_list_calls
Read-onlyIdempotent

List recorded calls from your workspace with optional date filtering. Returns call IDs, dates, participants, duration, and engagement metrics. Supports pagination for large result sets.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cursorNoPagination cursor from a previous response
toDateTimeNoEnd of date range (ISO 8601)
fromDateTimeNoStart of date range (ISO 8601, e.g. "2024-01-01T00:00:00Z")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "description": "Response from Gong API listing calls with optional pagination",
+  "type": "object"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "fromDateTime": "2024-01-01T00:00:00Z",
+    "toDateTime": "2024-01-31T23:59:59Z"
+  },
+  {
+    "cursor": "eyJvZmZzZXQiOiAxMDB9",
+    "fromDateTime": "2024-12-01T00:00:00Z"
+  }
+]
  3. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare safe, non-destructive, idempotent behavior. The description adds useful context about pagination and return fields, which goes beyond annotations. No contradictions.

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?

Two concise sentences, front-loaded with the main action and key features. Every word adds value, with no unnecessary details.

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?

Covers core functionality, optional filters, pagination, and return fields. Output schema exists, so return details are sufficient. Lacks potential limitations or default behavior, but overall complete for the tool's simplicity.

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 coverage is 100%, so the schema fully documents parameters. The description reinforces optional date filtering and pagination but does not add new semantic details beyond the schema's descriptions.

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 action (list), resource (recorded calls), scope (from workspace), and key features (date filtering, pagination, return fields). It is specific and helps distinguish from siblings like gong_get_call and gong_search_calls.

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?

The description implies usage through its examples but provides no explicit guidance on when to use this tool versus alternatives like gong_search_calls. It lacks instructions on prerequisites or exclusions.

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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TDQS

A3.9/5.0
Disambiguation4/5

Most tools have distinct purposes due to detailed descriptions, but there is potential confusion among the many Polymarket and pipeworx-related tools. The Gong-specific tools are clearly separated.

Naming Consistency3/5

Naming conventions are mixed: some use snake_case, others camelCase, and there is inconsistency between groups (e.g., gong_* vs. polymarket_*). However, within each subgroup, naming is consistent.

Tool Count2/5

35 tools is high for coherence. The server covers multiple domains (Gong calls, data research, betting), leading to an overloaded toolset that could be streamlined into fewer, more general tools.

Completeness4/5

The toolset is comprehensive for its intended use cases, covering Gong call management, a wide array of data lookups, and Polymarket betting analysis. Minor gaps exist, such as limited CRM features beyond calls.

Resources