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atlas_run_workflow

Run a saved or inline YAML workflow in Atlas to orchestrate LLM agents; supports dry-run, node overrides, and result persistence.

Instructions

运行工作流。同步阻塞到结束。

workflow_id 与 yaml 二选一(都传时以 yaml 为准):

  • workflow_id:运行已保存的 workflows/.yaml;

  • yaml:运行即时编写的自定义图全文,不落盘、不写 workflows/。 persist_as(可选):真实运行结束后,把 yaml 固化为 workflows/.yaml——新建要求 id 未被占用,更新需 expected_sha256 语义与 atlas_save_workflow 相同;dry_run 不固化。

attachments(可选,E-2A):运行附件 [{name, path}];path 是发起 机器本机绝对路径,启动前整读校验(单件 ≤16MiB/合计 ≤32MiB,名字 全小写且不得撞保留名/节点 id),内容字节克隆进 run 产物库后与原 文件再无关联。下游节点用 consumes 引用 name;投影只含摘要行, 原字节经界面产物工作台查看。响应不含原始路径。

node_overrides 是封闭的本次运行节点参数覆盖;不改 YAML,不接受权限或拓扑字段。 可覆盖:model/fallback/thinking/max_output_tokens/temperature/seed/ timeout_s/retry/prompt(llm)、max_turns/timeout_s/retry/prompt/workdir (coding_agent;research 无 workdir)、prompt(human)。 prompt 是完整替换本次运行的节点职责文本,不是追加; consumes/outputs/图结构永远不可覆盖——要长期生效就用 persist_as 固化 或调用 atlas_save_workflow。 dry_run=True 与真跑使用同一有效规格,只渲染、不花钱; 默认同步阻塞到结束(wait=true);wait=false 见下。dry_run=False 真实调用模型。暂停在 human 节点时返回 paused。 wait(默认 true)同步阻塞到结束;wait=false 通过全部预检与执行身份 断言后立即返回 run_id(status=starting),长任务不再占住会话—— 用 atlas_get_run 轮询、atlas_list_runs 列表。wait=false 与 persist_as 互斥(固化需要等真跑结束)。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYes
waitNo
yamlNo
dry_runNo
persist_asNo
attachmentsNo
workflow_idNo
node_overridesNo
expected_execution_sha256No

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so: it discloses cost behavior (dry_run=False actually calls models), blocking semantics, pause-at-human return value, attachment byte-cloning with size/name constraints, that raw attachment paths are excluded from the response, and the status=starting return for wait=false. This is unusually rich behavioral context.

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 purpose and blocking behavior are front-loaded, and the segment structure (one cluster per parameter) makes a long description scannable. The density is largely justified by 9 parameters, though some clauses could be tightened without loss.

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?

An output schema exists so return values need not be spelled out, and the description still adds useful response notes (no raw paths, paused status). Combined with the parameter and cost disclosures it is nearly complete; the unexplained required 'task' parameter is the one real hole for a tool of this complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and there are 9 parameters, so the description must compensate; it explains workflow_id, yaml, persist_as, attachments, node_overrides, dry_run, wait and references expected_sha256 semantics. However, the single required parameter 'task' is never mentioned or defined anywhere, leaving its meaning and expected content unresolved.

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?

States the specific verb+resource (run a workflow) and immediately qualifies the scope: synchronous blocking to completion, workflow_id vs inline yaml, and dry_run vs real execution. An agent can distinguish it from atlas_validate_workflow, atlas_save_workflow and atlas_resume_run without opening any schema.

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 routes the agent: workflow_id vs yaml (yaml wins if both), persist_as for long-term effect vs atlas_save_workflow, dry_run for rendering without cost, and wait=false for long jobs polled via atlas_get_run/atlas_list_runs. It also names the exclusion (wait=false is mutually exclusive with persist_as).

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