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Defines conventions for editing plan.json implementation plans, including task formats (T-X.Y IDs, complexity S/M/L), structured arrays, JSON escaping, and plan structure rules. Use when creating or modifying plan.json files.
How this skill is triggered — by the user, by Claude, or both
Slash command
/code:plan-editing-conventionsThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Conventions for creating and modifying implementation plans stored as `plan.json`.
Conventions for creating and modifying implementation plans stored as plan.json.
relative/path.ts)The plan is stored as plan.json with these key fields:
{
"content": "# Implementation Plan\n\n## Stage 1: ...\n\n### T-1.1: Task Title\n...",
"acceptanceCriteria": [...],
"pendingTasks": [...],
"completedTasks": [...],
"manualTasks": [...],
"openQuestions": [...],
"answeredQuestions": [...],
"gaps": [...],
"amendments": [...]
}
content: The full markdown plan as a JSON string with escaped newlines (\n). This is the human-readable plan text.CRITICAL: The content field is a JSON string. When editing:
\n escape sequences for newlines, NOT literal line breaksplan.md via the code:extract-plan-md skillTasks use the T-X.Y ID convention where X is the stage number and Y is the task number within that stage.
Each task in the plan content should follow this structure:
### T-X.Y: [Task Title]
**Files:** `path/to/file.ext`
**Complexity:** S | M | L
**AC Refs:** AC-001, AC-002
**Description:** Brief description of what this task accomplishes.
**Implementation Details:**
[Include one or more of the following as appropriate:]
**Mapping Table:** (for distribution/transformation tasks)
| Source | Target | Notes |
|--------|--------|-------|
| category_a | target_file_a.md | Section: XYZ |
| category_b | target_file_b.md | Section: ABC |
**Algorithm:** (for logic-heavy tasks)
1. Load input from `source_path`
2. Parse using `specific_method()`
3. For each item:
a. Transform using pattern X
b. Validate against schema Y
4. Write output to `target_path`
**Code Template:** (for new file creation)
```python
# Actual code structure to be created
from typing import TypedDict
class ConfigType(TypedDict):
field_a: str
field_b: int
def main_function(config: ConfigType) -> Result:
"""Docstring explaining purpose."""
pass
Before/After Example: (for modification tasks)
# BEFORE (current code)
def old_approach():
pass
# AFTER (with changes)
def new_approach():
# Added: explanation of change
pass
## Structured Array Format
### pendingTasks / completedTasks
```json
{
"id": "T-1.1",
"description": "Task description",
"acceptanceCriteria": ["AC-001", "AC-002"]
}
{
"timestamp": "2024-01-01T00:00:00",
"changes": ["Description of change 1", "Description of change 2"],
"conversation": [...]
}
Extract implementation details for tasks that involve:
Detail extraction checklist:
Skip detail extraction for:
When amending an existing plan:
content field and structured arrays as neededpendingTasks and completedTasks arraysplan.md via code:extract-plan-md after editsnpx claudepluginhub closedloop-ai/claude-plugins --plugin codeCreates structured implementation plans for multi-step tasks from specs or requirements. Generates plan.json and task markdown files with explicit code and testing steps.
Generates executable Markdown implementation plans for multi-step tasks from context briefs, resolving ambiguities, ordering dependencies, and enabling parallel worker execution.
Creates detailed implementation plans through interactive, iterative collaboration. Use when planning features, refactoring, or tasks with research and multi-agent analysis.