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Chat with the published agent

cs_chat

Send a message to a published Copilot Studio agent and return its replies, raw activities, and sign-in link; reuse conversationId to continue the same conversation.

Instructions

Send one utterance to the published agent and return its replies (and raw activities). Use conversationId to continue. If the agent answers with a sign-in card, signInUrl is returned.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
botIdNoAgent (bot) id. Defaults to workspace sync metadata or CPS_AGENT_ID.
maxMsNoHow long to wait for replies, ms (default 25000, kept under the client call budget)
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.
transportNoauto detects the agent's authentication mode via Dataverse; directline for no-auth/manual-auth agents; sdk for Entra SSO agents
utteranceYes
workspaceNoPath to (or inside) the agent workspace. Defaults to CPS_WORKSPACE or the current directory.
backgroundNoRun in the background and return a jobId immediately, then poll cs_job_status. MCP clients cut a tool call off after about 60 seconds; this operation can take much longer, and without this the work is orphaned rather than cancelled.
schemaNameNo
dataverseUrlNo
environmentIdNoPower Platform environment id (GUID). Defaults to workspace sync metadata or CPS_ENVIRONMENT_ID.
tokenEndpointNoExplicit DirectLine token endpoint
conversationIdNoContinue an earlier conversation from cs_chat
directLineSecretNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.1.8
    • removedInput schema / additionalProperties
      Removed value: -false
  2. First observedv0.1.5

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does disclose real behavior beyond the schema (return shape of replies/activities, the sign-in-card → signInUrl branch), but it is silent on auth requirements, the long-running/orphaning risk, and rate or timeout behavior that the agent would want to know.

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?

Three short sentences, front-loaded with purpose and then the continuation hint and the sign-in edge case. Every sentence carries information; the sign-in sentence is slightly peripheral but genuinely useful for a chat tool.

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?

For a 14-parameter tool with no annotations and no output schema, the description is thin: it never explains the authentication modes, defaults, or the background/jobId escape hatch that the schema also flags. It partially compensates by naming the response fields, but a caller still needs to open the schema to use it safely.

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 71%, so most parameters are already self-documented, including conversationId, whose description matches the sentence in the tool description. The description adds no syntax or format detail beyond the schema, so baseline 3 is appropriate.

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?

The description gives a precise verb+resource pair ('Send one utterance to the published agent and return its replies') and clarifies the return surface with 'and raw activities'. It is clearly distinguishable from transcript/evaluation siblings on intent, though it never names an alternative explicitly.

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?

'Use conversationId to continue' is the only usage directive, which implies the multi-turn pattern but never states when to pick cs_chat over cs_run_conversation_tests or how to start a fresh vs. resumed conversation. Context is implied rather than argued.

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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