Skip to main content
Glama

classify_calls_batch

Batch-classify unclassified calls on demand using OpenAI Moderation. Process up to 100 records per request for instant safety assessment.

Instructions

Batch safety-classify unclassified calls on demand (via OpenAI Moderation, POST /v1/safety-assessments/scan-batch). Complements the cron (every 15 min, 50 records) with a "right now" path — an AI agent can finish "classify all of last week's calls" in one prompt. Pro+ only (Free relies on the cron); the backend enforces the plan gate and budget gate. maxRecords (1-100, default 50); returns { scanned, assessed, flagged, failures, skipped }. Recorded with source='mcp' (distinguished from cron entries, so the dashboard can visualize on-demand classification). Audit: emits a safety.scan_batch_run event to the audit log.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
maxRecordsNoMax records scanned per request (1-100, default 50). Capped considering OpenAI's 1000 RPM limit and the 10s CPU/IO limit per worker request
Behavior5/5

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

No annotations provided, so the description must fully disclose behavior. It details the backend enforcement (plan gate, budget gate), limitations (maxRecords with 1-100 range and default 50), return format (scanned, assessed, flagged, failures, skipped), data lineage (source='mcp'), and audit event emission. 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.

Conciseness4/5

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

The description is moderately concise, with each sentence providing distinct value. It is front-loaded with the core purpose. A minor redundancy exists with the parameter default mentioned both in the description and schema, but overall well-structured.

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

Completeness5/5

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

Given no output schema, the description thoroughly explains the return values and side effects (audit event, source tracking). With only one parameter and clear usage context, it covers all necessary information for an agent to use the tool correctly.

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% for the single parameter maxRecords, with a detailed description including min/max/default and technical notes. The main description restates the default value but adds no significant new semantics beyond the schema. Baseline of 3 is appropriate.

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 performs batch safety classification of unclassified calls on demand, specifying the verb 'classify', resource 'unclassified calls', and method 'batch on demand'. It distinguishes itself from the cron job by offering a real-time path, making the purpose unmistakable.

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

Usage Guidelines5/5

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

Explicitly states when to use this tool ('right now' path for immediate classification) versus the cron job (every 15 min). Notes Pro+ plan requirement and that Free plan relies on cron. Provides a concrete example: 'classify all of last week's calls in one prompt', guiding agents on applicable scenarios.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/argosvix/mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server