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atlas_validate_workflow

Validate YAML workflow graphs before saving: checks syntax, node types, edge references, entry points, reachability, cycles, and field usage, returning JSON errors with path, line, and column.

Instructions

校验一份图定义(零成本)。传 yaml 全文,或已保存的 workflow_id。

检查:YAML 语法、节点类型封闭清单、边引用、条件边与路由字段、入口、 可达性、死环、有环必须设 max_iterations、consumes 引用、异质性提示。 返回 JSON;校验不过时 error 会指出具体字段或图结构问题,并统一附带 YAML path、line、column(整图聚合错误没有唯一坐标时只返回 path)。 按 workflow_id 校验时额外回显 yaml 原文与 file_sha256——修改已有图的 读-改-写闭环:改 yaml 内容后带 file_sha256 作为 expected_sha256 调 atlas_save_workflow。两个参数都传时以 yaml 全文为准。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yamlNo
workflow_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations present, the description carries the full burden and does so: it discloses zero cost, the full validation checklist, the error format including YAML path/line/column (and the path-only fallback for aggregate errors), and the extra echoed fields (yaml text, file_sha256) when validating by workflow_id. This is far beyond what the schema conveys.

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 cost note are front-loaded, and every subsequent sentence carries information (checks, error format, echo fields, precedence). It is dense but not padded; the long enumeration of checks is justified for a validator.

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?

An output schema exists so return values need not be explained, yet the description usefully adds error-format and echo-field detail. For a two-parameter validator in a sibling set that includes save/run/get, the description covers everything needed to invoke it correctly.

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

Parameters5/5

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, and it does: it explains the meaning of both empty-defaulted parameters, their two usage modes, the precedence rule when both are supplied, and the additional return content tied to workflow_id. That is meaningful semantic detail the bare schema lacks.

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 a specific verb and resource ('校验一份图定义') and then enumerates the exact checks performed (YAML syntax, node type closed list, edge references, conditional edges, entry, reachability, dead loops, max_iterations, consumes references). This distinguishes it clearly from siblings like atlas_save_workflow or atlas_run_workflow.

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 gives the two invocation modes (full yaml vs. saved workflow_id) and resolves the overlap by stating yaml text takes precedence when both are passed. It also names the correct downstream sibling and the exact handoff (pass file_sha256 as expected_sha256 to atlas_save_workflow), which is precisely the routing an agent needs.

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