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Summarise how the agent is doing in production

cs_summarize_transcripts

Summarize recent agent transcripts to reveal session outcomes, escalation rates, topic and tool usage, and questions behind failures, so you can prioritize what to fix next.

Instructions

Aggregate over recent sessions: how they ended, the escalation rate, average turns, how many never matched a topic, the topics and tools that actually fire, and the questions behind the sessions that went badly. Read-only. This is the input for deciding what to fix next, and for cs_create_test_set_csv fromTranscripts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topNoMaximum sessions to read (default 100, max 500)
daysNoWindow in days (default: everything returned)
topNNoHow many topics/tools/questions to list (default 10)
botIdNoAgent (bot) id. Defaults to workspace sync metadata or CPS_AGENT_ID.
clientIdNoEntra app (client) id for MSAL. Defaults to CPS_CLIENT_ID, then the first-party VS Code id.
tenantIdNoEntra tenant id. Defaults to the workspace sync metadata, then CPS_TENANT_ID.
workspaceNoPath to (or inside) the agent workspace. Defaults to CPS_WORKSPACE or the current directory.
environmentIdNoPower Platform environment id (GUID). Defaults to workspace sync metadata or CPS_ENVIRONMENT_ID.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.5

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations provided, the description carries the full disclosure burden and explicitly states 'Read-only,' which is the most safety-relevant behavior an agent needs to know. It also discloses that this is an aggregation operation rather than a per-session mutation, adding value beyond the schema.

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 a single dense paragraph with no fluff. It front-loads the key action ('Aggregate over recent sessions') and quickly covers what metrics are produced, state behavior, and downstream usage; slightly long but every clause earns its place.

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?

Despite no output schema, the description enumerates the return dimensions (how sessions ended, escalation rate, average turns, unmatched topics, topics/tools, and questions behind failures), which is sufficient for an agent to know what to invoke. It does not detail output shape, but the metric list is strong given the tool's analytic nature.

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% and every parameter has a description in the JSON schema. The description adds general context by explaining what the aggregated results measure, but it does not add additional per-parameter meaning beyond the schema's existing documentation.

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 uses a specific verb ('Aggregate') plus a concrete resource ('recent sessions') and enumerates exact metrics (escalation rate, average turns, unmatched topics, topics/tools that fire). It clearly distinguishes itself from sibling tools like cs_list_transcripts and cs_get_transcript by being an aggregate summary rather than a raw transcript reader.

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

Usage Guidelines4/5

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

The description clearly positions the tool as the input for deciding what to fix next and as a dependency for cs_create_test_set_csv fromTranscripts. While it does not enumerate explicit exclusions or alternatives, the stated purpose gives an agent enough context about when to reach for this tool over siblings.

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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