x-ipe-task-based-human-playground

name	x-ipe-task-based-human-playground
description	Create interactive examples for human validation. Human-initiated only — invoke ONLY when user explicitly requests a playground. Triggers on requests like "create playground", "human testing", "interactive demo", "I want to test this". Do NOT auto-suggest after feature_closing.

Task-Based Skill: Human Playground

Purpose

Execute Human Playground tasks by:

1. Creating runnable examples
2. Documenting usage instructions
3. Setting up and running test scenarios
4. Enabling human interaction

---

Important Notes

⚠️ HUMAN-INITIATED ONLY: This skill should ONLY be invoked when the human explicitly requests a playground (e.g., "create playground", "I want to test this interactively", "set up a demo"). It is NOT part of the standard engineering pipeline. The standard pipeline ends at feature_closing. Agents MUST NOT auto-suggest this skill as the next step after any pipeline stage.

BLOCKING: Learn x-ipe-workflow-task-execution skill before executing this skill.

Note: If Agent does not have skill capability, go to .github/skills/ folder to learn skills. SKILL.md is the entry point.

IMPORTANT: When process_preference.interaction_mode == "dao-represent-human-to-interact", NEVER stop to ask the human. Instead, call x-ipe-assistant-user-representative-Engineer to get the answer. The DAO skill acts as the human representative and will provide the guidance needed to continue.

---

Input Parameters

input:
  # Task attributes (from task board)
  task_id: "{TASK-XXX}"
  task_based_skill: "x-ipe-task-based-human-playground"

  # Execution context (passed by x-ipe-workflow-task-execution)
  execution_mode: "free-mode | workflow-mode"  # default: free-mode
  workflow:
    name: "N/A"  # workflow name, default: N/A
    extra_context_reference:  # optional, default: N/A for all refs
      specification: "path | N/A | auto-detect"
      impl-files: "path | N/A | auto-detect"

  # Task type attributes
  category: "standalone"
  next_task_based_skill:
    - skill: "x-ipe-task-based-feature-closing"
      condition: "Close feature after successful validation"
    - skill: "x-ipe-task-based-bug-fix"
      condition: "Fix bugs discovered during playground testing"
  process_preference:
    interaction_mode: "{from input process_preference.interaction_mode}"
  feature_phase: "Human Playground"

  # Required inputs

  # Context (from previous task or project)
  feature_id: "{FEATURE-XXX}"
  feature_title: "{title}"
  feature_version: "{version}"

Input Initialization

<input_init>
  <field name="task_id" source="x-ipe-tool-task-board-manager (auto-generated)" />
  <field name="execution_mode" source="x-ipe-workflow-task-execution (from --workflow-mode@{name})" />
  <field name="workflow.name" source="x-ipe-workflow-task-execution (from --workflow-mode@{name})" />
  <field name="process_preference.interaction_mode" source="from caller (x-ipe-workflow-task-execution) or default 'interact-with-human'" />
  <field name="feature_id" source="previous task output OR task board OR human input">
    <steps>
      1. IF previous task output contains feature_id → use it
      2. ELIF task board has feature_id in task data → use it
      3. ELSE → IF interaction_mode == "dao-represent-human-to-interact": derive from workflow context or x-ipe-assistant-user-representative-Engineer; ELSE: ask human for feature_id
    </steps>
  </field>
  <field name="feature_title" source="feature specification OR features.json">
    <steps>
      1. Query feature board for feature_id → extract title
      2. ELIF x-ipe-docs/features/{feature_id}/specification.md exists → extract title
      3. ELSE → IF interaction_mode == "dao-represent-human-to-interact": derive from feature_id context; ELSE: ask human
    </steps>
  </field>
  <field name="feature_version" source="features.json OR default '1.0.0'">
    <steps>
      1. Query feature board for feature_id → extract version
      2. ELIF not found → default to "1.0.0"
    </steps>
  </field>
</input_init>

---

Definition of Ready

<definition_of_ready>
  <checkpoint required="true">
    <name>Code implementation complete</name>
    <verification>Verify feature code is implemented and merged</verification>
  </checkpoint>
  <checkpoint required="true">
    <name>Feature status is "Done Code Implementation"</name>
    <verification>Check feature board for current status</verification>
  </checkpoint>
  <checkpoint required="true">
    <name>All tests passing</name>
    <verification>Run test suite and confirm zero failures</verification>
  </checkpoint>
</definition_of_ready>

---

Execution Flow

Step	Name	Action	Gate
1	Create Examples	Build runnable playground files in playground/	Playground file created
2	Document Usage	Add entry to playground/README.md	README updated
3	Create Tests	Write human simulation tests in playground/tests/	Test files created
4	Validate	Run playground command and verify exit code 0	Command succeeds
5	Run Tests	Execute human simulation tests	All tests pass
6	Complete	Verify DoD, output summary, inform human playground is ready	Playground delivered
7.1	Decide Next Action	DAO-assisted next task decision	Next action decided
7.2	Execute Next Action	Load skill, generate plan, execute	Execution started

BLOCKING: Step 4 is blocked until playground command runs without error. BLOCKING: Step 5 is blocked until human simulation tests pass. BLOCKING: Step 6 requires validation before Feature Closing (manual/stop_for_question: human validation; auto: skipped).

---

Execution Procedure

<procedure name="human-playground">
  <!-- CRITICAL: Both DoR/DoD check elements below are MANDATORY -->
  <execute_dor_checks_before_starting/>
  <schedule_dod_checks_with_sub_agent_before_starting/>

  <phase_0 name="Board — Register Task">
    <step_0_1>
      <name>Create Task on Board</name>
      <action>
        Call `x-ipe-tool-task-board-manager` → `task_create.py`:
        - task_type: "Human Playground"
        - description: summarize work from input context
        - status: "in_progress"
        - role: from input context
        - assignee: from input context
        Store returned task_id for later update.
      </action>
      <output>Task created on board with status in_progress</output>
    </step_0_1>
  </phase_0>

  <step_1>
    <name>Create Runnable Examples</name>
    <action>
      1. DETECT tech_stack from feature implementation files and project config
      2. TOOL SKILL ROUTING (config-filtered):
         a. DISCOVER: Scan .github/skills/x-ipe-tool-implementation-*/
         b. READ CONFIG: Read x-ipe-docs/config/tools.json → stages.feedback.human_playground
            - IF section missing/empty → config_active = false (all tools enabled)
            - ELSE → config_active = true (opt-in); force-enable general
         c. FILTER: IF config_active → only ENABLED tools participate
         d. SEMANTIC MATCH: Match tech_stack to enabled tool skill
         e. IF no match → fall back to Python defaults (.py, uv run python)
      3. DETERMINE file extension and run command from matched tool:
         - Python: ext=.py, cmd="uv run python"
         - TypeScript: ext=.ts, cmd="npx tsx"
         - JavaScript: ext=.js, cmd="node"
         - Java: ext=.java, cmd="java"
         - General: ext determined by context, cmd determined by context
      4. Create `playground/` directory if it does not exist
      5. Place playground files directly in `playground/` (no subfolders per feature)
      6. Name files as `playground_{feature_name}.{ext}` (dynamic extension)
      7. Identify key functionality to demonstrate
      8. Create minimal, self-contained runnable examples (happy path + edge cases)
    </action>
    <constraints>
      - BLOCKING: File naming must follow `playground_{feature_name}.{ext}` convention
      - CRITICAL: Examples must be self-contained and runnable without manual setup
    </constraints>
    <output>Playground file(s) in `playground/`, matched tool skill and run command</output>
  </step_1>

  <step_2>
    <name>Document Usage</name>
    <action>
      1. Create `README.md` inside `playground/` folder if it does not exist
      2. Add entry for the new playground with the command to run it
      3. Keep documentation minimal - explain how to run each playground
    </action>
    <constraints>
      - CRITICAL: README must include exact run command for each playground
    </constraints>
    <output>Updated `playground/README.md`</output>
  </step_2>

  <step_3>
    <name>Create and Validate Tests</name>
    <action>
      1. Create `playground/tests/` directory for test scripts
      2. Name test files as `test_playground_{feature_name}.{ext}` (same ext as Step 1)
      3. Write tests that simulate human interaction scenarios (NOT unit tests)
      4. Tests must validate expected behavior from a human perspective
    </action>
    <constraints>
      - CRITICAL: These are human simulation tests, not unit tests
      - BLOCKING: Test file naming must follow `test_playground_{feature_name}.{ext}`
    </constraints>
    <output>Test files in `playground/tests/`</output>
  </step_3>

  <step_4>
    <name>Validate Playground</name>
    <action>
      1. Execute playground using the run command determined in Step 1 (e.g., `uv run python`, `npx tsx`, `node`)
      2. Verify it runs without error (exit code 0)
      3. If it fails, fix the playground script or surrounding code
    </action>
    <success_criteria>
      - Playground command exits with code 0
      - No runtime errors or unhandled exceptions
    </success_criteria>
    <output>Verified working playground</output>
  </step_4>

  <step_5>
    <name>Run Tests</name>
    <action>
      1. Execute human simulation tests
      2. Verify all tests pass
      3. If tests fail, fix the playground or test scripts
    </action>
    <success_criteria>
      - All human simulation tests pass
    </success_criteria>
    <output>All tests passing</output>
  </step_5>

  <step_6>
    <name>Enable Interaction</name>
    <action>
      1. IF execution_mode == "workflow-mode":
         a. Run the workflow update script via bash (`python3 .github/skills/x-ipe-tool-x-ipe-app-interactor/scripts/workflow_update_action.py`) with:
            - workflow_name: {from context}
            - action: "human_playground"
            - status: "done"
            - feature_id: {feature_id}
            - deliverables: {"playground-url": "{path}"}
         b. Log: "Workflow action status updated to done"
      2. Provide start/stop commands
      3. Include sample data
      4. Add reset capability
      5. Log outputs for debugging
      6. Inform that playground is ready for testing

        Completion gate (based on interaction_mode):
        IF process_preference.interaction_mode == "dao-represent-human-to-interact":
          → Auto-proceed after DoD verification
        ELSE (interact-with-human/dao-represent-human-to-interact-for-questions-in-skill):
          → Ask human to validate playground
    </action>
    <output>Playground ready for human validation</output>
  </step_6>

  <step_6_1>
    <name>Update Task on Board</name>
    <action>
      Call `x-ipe-tool-task-board-manager` → `task_update.py`:
      - task_id: from Phase 0
      - status: "done"
      - output_links: list of deliverables produced in this skill execution
    </action>
    <output>Task marked done on board</output>
  </step_6_1>

  <phase_7 name="继续执行（Continue Execute）">
    <step_7_1>
      <name>Decide Next Action</name>
      <action>
        Collect the full context and task_completion_output from this skill execution.

        IF process_preference.interaction_mode == "dao-represent-human-to-interact":
          → Invoke x-ipe-assistant-user-representative-Engineer with:
            type: "routing"
            completed_skill_output: {full task_completion_output YAML from this skill}
            next_task_based_skill: "{from output}"
            context: "Skill completed. Study the context and full output to decide best next action."
          → DAO studies the complete context and decides the best next action
        ELSE (interact-with-human):
          → Present next task suggestion to human and wait for instruction
      </action>
      <constraints>
        - BLOCKING (manual): Human MUST confirm or redirect before proceeding
        - BLOCKING (auto): Proceed after DoD verification; auto-select next task via DAO
      </constraints>
      <output>Next action decided with execution context</output>
    </step_7_1>
    <step_7_2>
      <name>Execute Next Action</name>
      <action>
        Based on the decision from Step 7.1:
        1. Load the target task-based skill's SKILL.md
        2. Generate an execution plan from the skill's Execution Flow table
        3. Start execution from the skill's first phase/step
      </action>
      <constraints>
        - MUST load the skill before executing — do not skip skill loading
        - Execution follows the target skill's procedure, not this skill's
      </constraints>
      <output>Next task execution started</output>
    </step_7_2>
  </phase_7>

</procedure>

---

Output Result

task_completion_output:
  category: "standalone"
  status: completed | blocked
  next_task_based_skill:
    - skill: "x-ipe-task-based-feature-closing"
      condition: "Close feature after successful validation"
    - skill: "x-ipe-task-based-bug-fix"
      condition: "Fix bugs discovered during playground testing"
  process_preference:
    interaction_mode: "{from input process_preference.interaction_mode}"
  execution_mode: "{from input}"
  workflow:
    name: "{from input}"
  task_output_links:
    - "playground/playground_{feature_name}.{ext}"
    - "playground/tests/test_playground_{feature_name}.{ext}"
    - "playground/README.md"
  feature_id: "{FEATURE-XXX}"
  feature_title: "{title}"
  feature_version: "{version}"
  feature_phase: "Human Playground"

---

Definition of Done

CRITICAL: Use a sub-agent to validate DoD checkpoints independently.

<definition_of_done>
  <checkpoint required="true">
    <name>Runnable examples created</name>
    <verification>Verify playground/playground_{feature_name}.{ext} exists (ext from Step 1)</verification>
  </checkpoint>
  <checkpoint required="true">
    <name>README entry added</name>
    <verification>Verify playground/README.md contains run command for this feature</verification>
  </checkpoint>
  <checkpoint required="true">
    <name>Human simulation tests created</name>
    <verification>Verify playground/tests/test_playground_{feature_name}.{ext} exists</verification>
  </checkpoint>
  <checkpoint required="true">
    <name>Playground command verified</name>
    <verification>Agent has run playground command and confirmed exit code 0</verification>
  </checkpoint>
  <checkpoint required="true">
    <name>Human simulation tests pass</name>
    <verification>Agent has executed tests and confirmed all pass</verification>
  </checkpoint>
  <checkpoint required="true">
    <name>Human can interact with feature</name>
    <verification>Start/stop commands documented and sample data included</verification>
  </checkpoint>
</definition_of_done>

MANDATORY: After completing this skill, return to x-ipe-workflow-task-execution to continue the task execution flow.

---

Patterns & Anti-Patterns

Pattern: Standard Playground Structure

When: Creating any playground Then:

playground/
  README.md                               # How to run all playgrounds
  playground_{feature1}.{ext}             # Interactive playground (ext from tool skill)
  playground_{feature2}.{ext}             # Interactive playground
  tests/
    test_playground_{feature1}.{ext}      # Human simulation tests
    test_playground_{feature2}.{ext}      # Human simulation tests

Pattern: API/CLI Playground

When: Feature exposes an API or CLI Then: Same structure, include sample-data.json if needed for test data.

Anti-Patterns

Anti-Pattern	Why Bad	Do Instead
No instructions	Human cannot start	Write clear README
Hard-coded config	Does not work elsewhere	Use environment variables
No sample data	Nothing to test with	Provide seed data
Complex setup	Human gives up	Keep setup to 1-2 commands
No expected outputs	Human cannot tell if it works	Document what to expect

---

Examples

See references/examples.md for concrete execution examples.