AC dify-dsl-to-code
将 Dify 导出的工作流/Chatflow DSL 文件（YAML）转化为可部署、可运行的独立代码项目（默认 Python+FastAPI，可选 Node.js+Express）。当用户要求"Dify 工作流转代码"、"DSL 导出转项目"、"把 Dify 应用代码化"、"脱离 Dify 部署工作流"时使用。Convert an exported Dify workflow/chatflow DSL (YAML) into a deployable standalone code project. Use when the user asks to convert/export/translate a Dify DSL or .yml workflow file into runnable code, migrate off Dify, or self-host a Dify workflow as a service. 覆盖：读取用户指定路径的 DSL 文件、解析节点与变量依赖、就缺失信息（API Key、知识库语料、工具凭据、部署形态）与用户交互补全、超大 DSL 时拆解为功能块并派发给多智能体分块实现、最终拼接验证为完整项目。
将 Dify 导出的工作流/Chatflow DSL 文件（YAML）转化为可部署、可运行的独立代码项目（默认 Python+FastAPI，可选 Node.js+Express）。当用户要求"Dify 工作流转代码"、"DSL 导出转项目"、"把 Dify 应用代码化"、"脱离 Dify…
As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
How to improve
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 2
✓ No critical or high findings
Medium and low: 2
-
low Secrets in code
secret-high-entropy-tokenassets/examples/example-chatflow-qa.yml:446High-entropy token-like string (may be an id, hash or a credential) (test fixture / example file)- Yoel…Jmj+k8ao…Yx9
fixture -
low Secrets in code
secret-high-entropy-tokenassets/examples/example-chatflow-qa.yml:448High-entropy token-like string (may be an id, hash or a credential) (test fixture / example file)- haN99RBvZE/0V4pAo+qPCy…wRT
fixture
Files scanned: 29. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 52/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 60Tools and files. Uses tools (python, node) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 18 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 869 tokens
- 100Running it twice. No mutating operations
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 4 example trigger phrases
- +3Description length 525: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 18 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 96.