Claude Skill

compile-3d-workflow

Use when the user asks for direction and a compilable 3D workflow from an interview. Not for remote, credential, publish, deploy, or irreversible changes.

LLM Mart · 0 points · 0 views 0 listing impressions 0 install-command copies
Virus-scanned Reviewed automatically before listing.

Full trust report

Download outlinedriven-outline-driven-development-.devin_skills_compile-3d-workflow-b0e8ce8.zip · 1 KB
Part of outlinedriven/outline-driven-development — 145 skills

Install

skills CLI npx skills add https://github.com/OutlineDriven/outline-driven-development/tree/main/.devin/skills/compile-3d-workflow
Claude Code claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install outlinedriven-outline-driven-development@llmmart
Git git clone https://github.com/OutlineDriven/outline-driven-development.git

The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole outlinedriven/outline-driven-development collection as a plugin from our marketplace. Git is the plain clone.

Skill manifest

Compile 3D workflow

Contract

Field Bound contract
Trigger The user asks for direction and a compilable 3D workflow from an interview.
Authority Reversible local: writes only the named local 3D workflow artifact file; rollback is deleting that file. No remote mutation.
Side effect Writes one local 3D workflow artifact file.
Done A validated local 3D workflow artifact file exists and passes every structural check.

Inputs

  • A direction interview with the user, supplying: the problem being solved, what success looks like, binding constraints, and what is explicitly out of scope. All four required; none inferred.
  • The output file path for the workflow artifact. Required.

Artifact schema

The workflow artifact is a YAML file with this structure:

problem: <string>
success_criteria: <string>
constraints: [<string>, ...]
out_of_scope: [<string>, ...]
topology:
  nodes:
    - id: <string>
      task: <string>
      depends_on: [<node_id>, ...]
ontology:
  groups:
    - name: <string>
      members: [<node_id>, ...]
feedback_loops:
  - name: <string>
    sensor: <string>
    comparator: <string>
    actuator: <string>

Every node id referenced in depends_on must exist in nodes. Every node id in ontology group members must exist in nodes. Every feedback loop must name a sensor, comparator, and actuator as non-empty strings.

Procedure

  1. Conduct the direction interview. Ask the user for the problem, success criteria, binding constraints, and explicit out-of-scope. Record the answers verbatim. Done when: all four interview inputs are recorded verbatim, or the missing input is named and the skill stops.
  2. Author the workflow artifact from the interview answers. Build the three dimensions:
    • Topology: a DAG of tasks. Each node has an id, a task description, and a depends_on list naming the node ids it waits on. No cycles. No node depends on itself. Every depends_on entry must reference an existing node id.
    • Ontology groups: named concept clusters classifying the work domains. Each group names its member node ids. Every group is non-empty. Every member must exist in the topology.
    • Feedback loops: cybernetic control cycles. Each loop names its sensor (what is measured), comparator (what is expected), and actuator (what action re-routes). All three are non-empty strings. Done when: the artifact combines all three dimensions from the interview answers.
  3. Validate the artifact against the schema. Check every rule:
    • Every node has a unique id and a non-empty task.
    • Every depends_on entry references an existing node id.
    • No cycle exists in the dependency graph (topological sort succeeds).
    • Every ontology group is non-empty and every member references an existing node id.
    • Every feedback loop names a non-empty sensor, comparator, and actuator. Done when: every check passes, or the specific defect is named and the skill stops.
  4. Write the validated artifact to the output file path as YAML. State the rollback path: delete the local artifact file. No remote state was touched. Done when: the artifact file is written and the rollback path is stated.

Failure and recovery

  • Interview incomplete: if the user cannot supply the problem, success criteria, constraints, or scope, stop and report which inputs are missing. Do not infer or fabricate direction.
  • Schema validation failure: if any node lacks dependencies, any ontology group is empty, any feedback loop is missing its sensor, comparator, or actuator, any depends_on entry references a non-existent node, or a cycle exists in the dependency graph, report the specific defect and stop. Do not emit a partial artifact as complete.
  • Partial-result rule: a partially written artifact file is not a compiled workflow. Delete it and report the rollback.

Output

A validated local 3D workflow artifact file (YAML) containing the DAG topology, ontology groups, and feedback loops, with every structural check passing.

Files (outline-driven-development)
  • agents
    • openai.yaml 157 B
      interface:
        display_name: "Compile 3d Workflow"
        short_description: "Use when the user asks for direction and a compilable 3D workflow from an interview."
      
  • SKILL.md 4.1 KB
    ---
    name: compile-3d-workflow
    description: 'Use when the user asks for direction and a compilable 3D workflow from an interview. Not for remote, credential, publish, deploy, or irreversible changes.'
    ---
    
    # Compile 3D workflow
    
    ## Contract
    
    | Field | Bound contract |
    |---|---|
    | Trigger | The user asks for direction and a compilable 3D workflow from an interview. |
    | Authority | Reversible local: writes only the named local 3D workflow artifact file; rollback is deleting that file. No remote mutation. |
    | Side effect | Writes one local 3D workflow artifact file. |
    | Done | A validated local 3D workflow artifact file exists and passes every structural check. |
    
    ## Inputs
    
    - A direction interview with the user, supplying: the problem being solved, what success looks like, binding constraints, and what is explicitly out of scope. All four required; none inferred.
    - The output file path for the workflow artifact. Required.
    
    ## Artifact schema
    
    The workflow artifact is a YAML file with this structure:
    
    ```yaml
    problem: <string>
    success_criteria: <string>
    constraints: [<string>, ...]
    out_of_scope: [<string>, ...]
    topology:
      nodes:
        - id: <string>
          task: <string>
          depends_on: [<node_id>, ...]
    ontology:
      groups:
        - name: <string>
          members: [<node_id>, ...]
    feedback_loops:
      - name: <string>
        sensor: <string>
        comparator: <string>
        actuator: <string>
    ```
    
    Every node id referenced in `depends_on` must exist in `nodes`. Every node id in ontology group `members` must exist in `nodes`. Every feedback loop must name a sensor, comparator, and actuator as non-empty strings.
    
    ## Procedure
    
    1. Conduct the direction interview. Ask the user for the problem, success criteria, binding constraints, and explicit out-of-scope. Record the answers verbatim. Done when: all four interview inputs are recorded verbatim, or the missing input is named and the skill stops.
    2. Author the workflow artifact from the interview answers. Build the three dimensions:
       - Topology: a DAG of tasks. Each node has an id, a task description, and a depends_on list naming the node ids it waits on. No cycles. No node depends on itself. Every depends_on entry must reference an existing node id.
       - Ontology groups: named concept clusters classifying the work domains. Each group names its member node ids. Every group is non-empty. Every member must exist in the topology.
       - Feedback loops: cybernetic control cycles. Each loop names its sensor (what is measured), comparator (what is expected), and actuator (what action re-routes). All three are non-empty strings.
       Done when: the artifact combines all three dimensions from the interview answers.
    3. Validate the artifact against the schema. Check every rule:
       - Every node has a unique id and a non-empty task.
       - Every depends_on entry references an existing node id.
       - No cycle exists in the dependency graph (topological sort succeeds).
       - Every ontology group is non-empty and every member references an existing node id.
       - Every feedback loop names a non-empty sensor, comparator, and actuator.
       Done when: every check passes, or the specific defect is named and the skill stops.
    4. Write the validated artifact to the output file path as YAML. State the rollback path: delete the local artifact file. No remote state was touched. Done when: the artifact file is written and the rollback path is stated.
    
    ## Failure and recovery
    
    - Interview incomplete: if the user cannot supply the problem, success criteria, constraints, or scope, stop and report which inputs are missing. Do not infer or fabricate direction.
    - Schema validation failure: if any node lacks dependencies, any ontology group is empty, any feedback loop is missing its sensor, comparator, or actuator, any depends_on entry references a non-existent node, or a cycle exists in the dependency graph, report the specific defect and stop. Do not emit a partial artifact as complete.
    - Partial-result rule: a partially written artifact file is not a compiled workflow. Delete it and report the rollback.
    
    ## Output
    
    A validated local 3D workflow artifact file (YAML) containing the DAG topology, ontology groups, and feedback loops, with every structural check passing.
    

Comments (0)

Sign in to join the conversation.

No comments yet.

Reviews (0)

No reviews yet.

Related