Orchestration MCP
Orchestration MCP
用于启动和跟踪外部编码代理运行的 TypeScript MCP 服务器。
MCP 接口保持稳定,而内部执行后端可以针对:
本地
codex本地
claude_code远程
remote_a2a
这使得顶层代理可以调用一套 MCP 工具,而编排层决定子代理是本地 SDK 进程还是远程 A2A 兼容代理。
安装与构建
cd orchestration-mcp
npm install
npm run buildRelated MCP server: mcpcodeserver
运行 MCP 服务器
cd orchestration-mcp
npm start这将从 dist/index.js 启动 MCP 服务器。
Codex MCP 配置示例
如果您希望 Codex 加载此 MCP 服务器,请在 ~/.codex/config.toml 中添加如下条目:
[mcp_servers.orchestration-mcp]
command = "node"
args = ["/abs/path/to/orchestration-mcp/dist/index.js"]
enabled = true使用此仓库路径的示例:
[mcp_servers.orchestration-mcp]
command = "node"
args = ["/Users/fonsh/PycharmProjects/Treer/nanobot/orchestration-mcp/dist/index.js"]
enabled = true更新配置后,重启 Codex 以重新加载 MCP 服务器。
MCP 公开的内容
服务器注册了以下工具:
spawn_runget_runpoll_eventscancel_runcontinue_runlist_runsget_event_artifact
典型的 MCP 流程
调用
spawn_run创建子代理运行。调用
poll_events直到看到终端事件或等待状态。如果运行进入
input_required或auth_required,调用continue_run。调用
get_run获取最新的运行摘要。如果事件包含
artifact_refs,调用get_event_artifact以获取完整负载。
spawn_run 注意事项
backend:"codex"、"claude_code"或"remote_a2a"role: 编排角色标签,例如planner、worker或reviewerprompt: 简单运行的纯文本指令input_message: 用于多部分/A2A 风格输入的可选结构化消息cwd: 绝对工作目录session_mode:new或resumesession_id: 恢复先前会话时必需profile: 可选的个人资料/职位描述文件路径。提供后,编排器会加载该文件并将其注入代理上下文。具有原生系统提示支持的后端会在那里使用它;其他后端将其预置到运行上下文中。
除非明确指示使用配置文件,否则请将 profile 留空。
output_schema: 用于结构化最终输出的可选 JSON Schemametadata: 为关联和审计存储的可选编排元数据backend_config: 可选的后端特定设置。对于remote_a2a,请在此处设置agent_url和任何身份验证标头/令牌。
对于所有后端,cwd 是用于运行/会话存储的编排侧工作目录。
对于 remote_a2a,spawn_run.cwd 也会转发给远程子代理,并成为该 A2A 任务上下文的执行目录。
prompt 或 input_message 至少需要提供一个。
简单示例:
{
"backend": "codex",
"role": "worker",
"prompt": "Inspect the repository and summarize the architecture.",
"cwd": "/abs/path/to/project",
"session_mode": "new"
}远程 A2A 示例:
{
"backend": "remote_a2a",
"role": "worker",
"prompt": "Inspect the repository and summarize the architecture.",
"cwd": "/abs/path/to/project",
"session_mode": "new",
"backend_config": {
"agent_url": "http://127.0.0.1:53552"
}
}审阅者工作流资产
此仓库包含一个用于多代理编码工作流的现成审阅者设置:
profile:
./profile/reviewer-remediator.md
推荐用于审阅者运行的 spawn_run 用法:
{
"backend": "codex",
"role": "reviewer",
"cwd": "/abs/path/to/project",
"session_mode": "new",
"profile": "/abs/path/to/orchestration-mcp/profile/reviewer-remediator.md",
"prompt": "Review only the latest diff in the current working directory, apply low-risk fixes when clearly correct, validate them, and write a remediation report."
}continue_run 注意事项
当运行进入 input_required 或 auth_required 且后端支持交互式继续时,请使用 continue_run。
输入:
run_idinput_message
get_event_artifact 注意事项
当 poll_events 返回的已清理事件包含 event.data.artifact_refs 且您需要完整的原始负载时,请使用 get_event_artifact。
输入:
run_idseqfield_path: 相对于event.data的 JSON 指针,例如/stdout、/raw_tool_use_result或/input/contentoffset: 可选字节偏移量,默认为0limit: 可选字节限制,默认为65536
典型流程:
调用
poll_events。检查任何已清理事件上的
event.data.artifact_refs。使用相同的
run_id、事件seq和公开的field_path值之一调用get_event_artifact。
后端默认值
codex: 使用当前的@openai/codex-sdk默认值,加上适配器中已连接的非交互式执行设置claude_code: 使用带有permissionMode: "bypassPermissions"的@anthropic-ai/claude-agent-sdk,以便 MCP 调用保持非阻塞,并为resume重用持久化的后端会话 IDremote_a2a: 使用@a2a-js/sdk连接到远程 A2A 兼容代理,将任务更新流式传输到规范化的编排事件中,并支持input_required的continue_run
对于 claude_code,请确保在测试前本地环境已具备有效的 Claude Code 身份验证设置。
测试 A2A 代理
该仓库包含用于本地 A2A 封装测试代理的辅助模块:
dist/test-agents/codex-a2a-agent.jsdist/test-agents/claude-a2a-agent.jsdist/test-agents/start-a2a-agent.js
这些模块导出了启动辅助程序,将本地 Codex 和 Claude SDK 封装在 A2A 服务器之后,以便编排 MCP 可以针对真实的子代理测试其内部的 remote_a2a 后端。
要启动交互式封装启动器:
npm run start:a2a-agent脚本将询问是封装 codex 还是 claude_code。
启动后,它会打印 agent_url 和一个可供 MCP 层使用的 spawn_run 负载。封装器在启动时不再锁定工作目录。每个 remote_a2a 调用都使用提供给 spawn_run 的 cwd,并且封装器在同一个 A2A contextId 的生命周期内保持该 cwd 不变。
存储
运行数据存储在:
<cwd>/.nanobot-orchestrator/
runs/
<run_id>/
run.json
events.jsonl
result.json
artifacts/
000008-command_finished/
manifest.json
stdout.0001.txt
stdout.0002.txt
sessions/
<session_id>.json注意事项:
events.jsonl存储旨在供poll_events使用的已清理事件。超大的原始负载被移动到每个事件的工件文件中,并从
event.data.artifact_refs中引用。run.json和result.json保留当前的运行快照和最终结果行为。为了与现有实现向后兼容,存储目录名称目前为
.nanobot-orchestrator/。
Available Tools
7 toolscancel_runB
Cancel a running external coding-agent run.
| Name | Required | Description | Default |
|---|---|---|---|
| run_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| run_id | Yes | |
| status | Yes | |
| cancelled_at | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('cancel') but doesn't explain what cancellation entails (e.g., whether it's reversible, if it stops processes immediately, what permissions are required, or any side effects like resource cleanup). For a mutation tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the key action and target, making it efficient and easy to parse. Every word earns its place, with no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a mutation with one parameter) and the presence of an output schema (which handles return values), the description is minimally adequate. However, with no annotations and low schema coverage, it lacks details on behavioral aspects like side effects or error conditions. It meets the basic requirement but leaves gaps in understanding the tool's full context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter ('run_id') with 0% description coverage, meaning the schema provides no semantic details. The description doesn't add any information about this parameter (e.g., what a 'run_id' is, how to obtain it, or format examples). However, with only one parameter, the baseline is higher; the description implies the parameter identifies the run to cancel but doesn't compensate for the lack of schema details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('cancel') and the target ('a running external coding-agent run'), which is specific and unambiguous. It distinguishes from siblings like 'continue_run' or 'get_run' by focusing on termination rather than continuation or retrieval. However, it doesn't explicitly differentiate from all siblings (e.g., 'spawn_run' is about creation, but this isn't stated).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., that the run must be active), exclusions (e.g., not for completed runs), or comparisons to siblings like 'continue_run' for ongoing runs or 'list_runs' for status checks. This leaves the agent to infer usage context from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
continue_runB
Send an additional input message to a run that is waiting for more input.
| Name | Required | Description | Default |
|---|---|---|---|
| run_id | Yes | ||
| input_message | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| run_id | Yes | |
| status | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While it correctly indicates a write operation ('send'), it lacks critical details: required permissions, whether this changes run state, rate limits, error conditions, or what happens after sending input. For a mutation tool with complex nested parameters, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every word earns its place, making it maximally concise while still conveying the essential action and context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters with nested objects), no annotations, but presence of an output schema, the description is minimally adequate. The output schema reduces need to describe return values, but the description should provide more context about run states, prerequisites, and parameter meanings to be truly complete for this interactive operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate but provides no parameter information. It doesn't explain what 'run_id' refers to, the structure of 'input_message', valid roles, or part types. With 2 parameters including complex nested objects, the description fails to add any semantic value beyond what the bare schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('send an additional input message') and target ('to a run that is waiting for more input'), providing specific verb+resource. However, it doesn't explicitly differentiate from sibling tools like 'spawn_run' or 'cancel_run', which would require mentioning it's for existing runs in a waiting state rather than creating new runs or terminating them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by specifying 'to a run that is waiting for more input', suggesting this tool should be used when a run is in a specific state. However, it doesn't provide explicit when-not-to-use guidance or name alternatives like 'spawn_run' for new runs or 'cancel_run' for termination, leaving some ambiguity about sibling tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_event_artifactC
Read a sanitized event artifact by run_id, seq, and JSON Pointer field_path.
| Name | Required | Description | Default |
|---|---|---|---|
| run_id | Yes | ||
| seq | Yes | ||
| field_path | Yes | ||
| offset | No | ||
| limit | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| seq | Yes | |
| mime | Yes | |
| offset | Yes | |
| run_id | Yes | |
| content | Yes | |
| relpath | Yes | |
| encoding | Yes | |
| has_more | Yes | |
| field_path | Yes | |
| total_bytes | Yes | |
| returned_bytes | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states it's a read operation. It doesn't disclose behavioral traits like authentication requirements, rate limits, error conditions, what 'sanitized' means, or how the JSON Pointer field_path works. The mention of 'sanitized' hints at data transformation but lacks details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise single sentence with zero wasted words. Front-loaded with the core purpose, and every element (verb, resource, parameters) earns its place. No structural issues despite the brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters with 0% schema coverage and no annotations, the description is incomplete—it doesn't explain parameter semantics or behavioral context. However, the existence of an output schema reduces the need to describe return values. For a read operation, this is minimally adequate but leaves important gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate but only lists parameter names without explaining their meaning. It mentions 'run_id, seq, and JSON Pointer field_path' but doesn't clarify what these identifiers represent, what 'offset' and 'limit' do, or how field_path syntax works. This leaves significant gaps in parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Read') and resource ('sanitized event artifact') with specific identifiers (run_id, seq, field_path). It distinguishes from siblings like get_run or list_runs by focusing on artifacts rather than runs themselves. However, it doesn't explicitly contrast with poll_events which might also retrieve event data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like poll_events or get_run. The description mentions parameters but doesn't provide context about appropriate use cases, prerequisites, or when other tools might be more suitable. This leaves the agent without clear decision criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_runB
Get the current summary status for a known run.
| Name | Required | Description | Default |
|---|---|---|---|
| run_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| cwd | Yes | |
| role | Yes | |
| run_id | Yes | |
| status | Yes | |
| backend | Yes | |
| summary | Yes | |
| last_seq | Yes | |
| metadata | Yes | |
| remote_ref | Yes | |
| session_id | Yes | |
| started_at | Yes | |
| updated_at | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves a 'summary status,' implying a read-only operation, but doesn't specify whether it's safe, if it requires authentication, rate limits, or what happens if the run_id is invalid. For a tool with no annotations, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero waste: 'Get the current summary status for a known run.' It is front-loaded and efficiently conveys the core purpose without unnecessary elaboration, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter, no nested objects) and the presence of an output schema (which handles return values), the description is minimally adequate. However, with no annotations and incomplete parameter semantics, it lacks details on behavioral traits and usage context, making it only partially complete for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter (run_id) with 0% description coverage, meaning the schema provides no semantic details. The description adds minimal context by implying 'run_id' refers to 'a known run,' but doesn't explain format, examples, or constraints. This partially compensates for the schema gap, but not fully, aligning with the baseline for moderate coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get the current summary status for a known run.' It specifies the verb ('Get'), resource ('summary status'), and scope ('for a known run'), which is specific and actionable. However, it doesn't explicitly differentiate from sibling tools like 'list_runs' or 'poll_events', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions 'a known run' but doesn't clarify prerequisites (e.g., that the run must already exist from a previous operation) or contrast it with siblings like 'list_runs' (for listing runs) or 'poll_events' (for monitoring events). This leaves the agent without explicit usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_runsC
List runs known to the current orchestration MCP process.
| Name | Required | Description | Default |
|---|---|---|---|
| status | No | ||
| backend | No | ||
| cwd | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| runs | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but discloses minimal behavioral traits. It indicates this is a listing operation but doesn't describe pagination, sorting, default behavior, rate limits, or authentication needs. For a tool with 3 parameters and no annotation coverage, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded with the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which handles return values), the description's minimalism is partially acceptable. However, with 3 parameters, no annotations, and 0% schema coverage, the description should provide more context about filtering behavior and usage scenarios to be truly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate but adds no parameter information. It doesn't explain what 'status', 'backend', or 'cwd' mean, their relationships, or how they filter results. With 3 parameters (2 with enums) undocumented, this is a significant gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('runs'), and specifies the scope ('known to the current orchestration MCP process'). However, it doesn't explicitly differentiate from sibling tools like 'get_run' or 'poll_events', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_run' (for single run details) or 'poll_events' (for event monitoring). It mentions the scope but offers no explicit when/when-not instructions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
poll_eventsB
Long-poll incremental events for a run after a known sequence number.
| Name | Required | Description | Default |
|---|---|---|---|
| run_id | Yes | ||
| after_seq | Yes | ||
| limit | No | ||
| wait_ms | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| events | Yes | |
| run_id | Yes | |
| status | Yes | |
| next_after_seq | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It mentions 'Long-poll' and 'incremental events,' hinting at real-time behavior and potential waiting, but lacks details on rate limits, authentication needs, error handling, or what 'events' entail. This leaves significant behavioral gaps for an agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads key information ('Long-poll incremental events') without unnecessary words. Every part earns its place by specifying the action, resource, and key parameter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters with 0% schema coverage, no annotations, but an output schema exists, the description is moderately complete. It covers the core purpose and one parameter but misses details on other parameters, behavioral traits, and usage context. The output schema helps, but more guidance is needed for effective tool use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It explains 'after_seq' as 'after a known sequence number,' adding context beyond the schema's numeric constraints. However, it doesn't cover other parameters like run_id, limit, or wait_ms, leaving them undocumented. Baseline is 3 due to partial compensation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Long-poll incremental events') and resource ('for a run'), specifying it retrieves events after a known sequence number. It distinguishes from siblings like get_event_artifact or get_run by focusing on incremental polling rather than direct fetching, though it doesn't explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for monitoring incremental events in a run after a specific sequence, suggesting it's for real-time updates. However, it doesn't explicitly state when to use this vs. alternatives like get_event_artifact or list_runs, nor does it mention prerequisites like needing an active run.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
spawn_runB
Start a new external coding-agent run and return immediately.
| Name | Required | Description | Default |
|---|---|---|---|
| backend | Yes | Backend to execute the run. Supported values are "codex", "claude_code", and "remote_a2a". | |
| role | Yes | Supervisor role for this run: planner, worker, or reviewer. | |
| prompt | No | Primary instruction for the coding agent run. | |
| input_message | No | Structured input message for multi-part or A2A-compatible runs. | |
| cwd | Yes | Absolute working directory where the agent should run and where artifacts are stored. | |
| session_mode | Yes | Use "new" to create a fresh session or "resume" to continue an existing one. | |
| session_id | No | ||
| profile | No | Optional path to a profile/persona/job-description file. Leave blank unless explicitly instructed to use a profile. | |
| output_schema | No | Optional JSON Schema for structured final output from the run. | |
| metadata | No | Optional orchestration metadata for task/step correlation. It is stored but not interpreted by the MCP server. | |
| backend_config | No | Optional backend-specific configuration, such as remote_a2a agent_url and auth headers. |
Output Schema
| Name | Required | Description |
|---|---|---|
| role | Yes | |
| run_id | Yes | |
| status | Yes | |
| backend | Yes | |
| session_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. 'Start a new external coding-agent run' implies a write/mutation operation, but the description doesn't disclose permission requirements, rate limits, whether this consumes resources, what happens to previous runs, or how to monitor the started run. 'Return immediately' suggests asynchronous execution but lacks details about how to track completion or retrieve results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single sentence that communicates the core action and key behavioral trait ('return immediately'). There's zero wasted language, and it's front-loaded with the essential information. Every word earns its place in this minimal description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex tool with 11 parameters, nested objects, and no annotations, the description is minimal. While an output schema exists (reducing need to describe return values), the description doesn't address the tool's role in the broader workflow with sibling tools, doesn't explain the asynchronous nature hinted by 'return immediately', and provides no context about error conditions or typical usage patterns. It's adequate but leaves significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 91% schema description coverage, the schema does most of the parameter documentation work. The description adds no parameter-specific information beyond what's in the schema. It doesn't explain relationships between parameters (like how 'session_mode' interacts with 'session_id'), typical values, or usage patterns. The baseline of 3 is appropriate given the high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Start a new external coding-agent run') and resource ('coding-agent run'), with the specific behavioral detail 'and return immediately' distinguishing it from potentially blocking operations. However, it doesn't explicitly differentiate from sibling tools like 'continue_run' or 'get_run' beyond the 'start new' aspect.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal guidance - only that it starts a new run and returns immediately. There's no explicit guidance on when to use this versus alternatives like 'continue_run' for resuming sessions, 'cancel_run' for stopping runs, or 'poll_events' for monitoring. No prerequisites, constraints, or typical use cases are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
7 tool updates
v0.1.0- First observed
cancel_run - First observed
continue_run - First observed
get_event_artifact - First observed
get_run - First observed
list_runs - First observed
poll_events - First observed
spawn_run
TDQS
Scored across 7 tools
Each tool has a clearly distinct purpose with no overlap: cancel_run stops a run, continue_run sends input, get_event_artifact reads artifacts, get_run retrieves status, list_runs enumerates runs, poll_events monitors events, and spawn_run initiates runs. The descriptions make it easy to distinguish between status retrieval, event handling, run management, and input/output operations.
All tool names follow a consistent verb_noun pattern with snake_case, such as cancel_run, get_run, list_runs, and spawn_run. This uniformity makes the set predictable and easy to navigate, with no deviations in style or structure across the seven tools.
With 7 tools, the count is well-scoped for an orchestration server focused on managing external coding-agent runs. Each tool serves a specific function in the lifecycle of runs, from creation to monitoring and termination, without being overly sparse or bloated, fitting typical orchestration needs.
The tool set provides complete coverage for the orchestration domain: it supports the full lifecycle of runs with spawn_run (create), get_run and list_runs (read), continue_run (update input), and cancel_run (delete/terminate), plus event handling with poll_events and get_event_artifact. There are no obvious gaps, enabling agents to manage runs effectively from start to finish.
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