Skip to main content
Glama

Send TraeCN Task

traecn_send_message

Delegate coding tasks to TraeCN by submitting one instruction as durable background work, returning a stable taskId for tracking without follow-up probes.

Instructions

Submit one user instruction to TraeCN as durable background work and return its stable taskId immediately; the gateway owns queueing, retries, recovery, and result persistence. Use this for every delegated coding request, optionally targeting an existing conversation via conversationId. Do not send follow-up messages to probe progress — track the returned task instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageYesThe exact instruction to execute.
conversationIdNoStable identifier returned by traecn_list_conversations.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okNoFalse when the gateway rejected the submission.
codeNoStable machine-readable result or error code.
errorNoError identifier or diagnostic when the operation failed.
statusNoAcceptance status reported by the gateway.
taskIdNoStable identifier used by traecn_get_task and traecn_cancel_task.
changedNoWhether visible TraeCN state changed.
messageNoHuman-readable outcome summary.
successNoWhether the operation succeeded.
retryableNoWhether retrying the same call can succeed later.
nextActionNoSuggested next step after a failure.
conversationIdNoStable TraeCN conversation identifier.
Behavior4/5

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

Annotations already indicate readOnlyHint=false, but the description adds meaningful behavioral context: it is durable background work, the gateway owns queueing, retries, recovery, and result persistence, and it returns immediately. This goes beyond what annotations convey and helps the agent understand the async nature and reliability guarantees. Not contradictory to annotations, and adds value beyond them.

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 with no filler. The first sentence states the core purpose and behavior (submit and return taskId, background work, gateway owns lifecycle), and the second gives usage guidance (use for every delegated request, optionally target conversation, do not probe). The key information is front-loaded and every phrase earns its place.

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 the tool's simplicity (2 params, 1 required), existing output schema, and annotations covering safety, the description is fully sufficient. It covers when to use, the async/durable behavior, how to handle the response (track the task), and the optional conversationId context. An agent has everything needed to invoke it correctly without further investigation.

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 both parameters are already documented. The description adds a small amount of usage context, such as 'optionally targeting an existing conversation via conversationId,' but this is largely redundant with the schema description for conversationId. The description does not clarify any additional syntax or format beyond the schema, so a baseline score 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 verb (submit), the resource (one user instruction to TraeCN), and the outcome (return a stable taskId immediately). It also frames this as the primary tool for delegated coding requests, distinguishing it from sibling tools that track or cancel tasks. This is specific and unambiguous.

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?

The description explicitly says 'Use this for every delegated coding request,' providing a clear when-to-use condition. It also warns against using it to probe progress ('Do not send follow-up messages to probe progress') and directs the agent to track the returned task instead, implicitly routing to the appropriate sibling (traecn_get_task). This is decisive guidance.

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/Luckycat133/traecnclaw-mcp-skill'

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