create-rule
Create Cursor rules for persistent AI guidance. Use when the user wants to create a rule, add coding standards, set up project conventions, configure…
Use when you have a spec or requirements for a multi-step task, before touching code
$ npx -y skills add coco-research/coco --skill writing-plans --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/writing-plansContext preview
The summary Claude sees to decide when to auto-load this skill.
Use when you have a spec or requirements for a multi-step task, before touching code
name: writing-plans description: Use when you have a spec or requirements for a multi-step task, before touching code domain: foundational
Write comprehensive implementation plans assuming the engineer has zero context for our codebase and questionable taste. Document everything they need to know: which files to touch for each task, code, testing, docs they might need to check, how to test it. Give them the whole plan as bite-sized tasks. DRY. YAGNI. TDD. Frequent commits.
Assume they are a skilled developer, but know almost nothing about our toolset or problem domain. Assume they don't know good test design very well.
**Announce at start:** "I'm using the writing-plans skill to create the implementation plan."
**Context:** This should be run in a dedicated worktree (created by brainstorming skill).
**Save plans to:** `docs/superpowers/plans/YYYY-MM-DD-<feature-name>.md`
If the spec covers multiple independent subsystems, it should have been broken into sub-project specs during brainstorming. If it wasn't, suggest breaking this into separate plans — one per subsystem. Each plan should produce working, testable software on its own.
Before defining tasks, map out which files will be created or modified and what each one is responsible for. This is where decomposition decisions get locked in.
This structure informs the task decomposition. Each task should produce self-contained changes that make sense independently.
**Each step is one action (2-5 minutes):**
**Every plan MUST start with this header:**
# [Feature Name] Implementation Plan > **For agentic workers:** REQUIRED: Use superpowers:subagent-driven-development (if subagents available) or superpowers:executing-plans to implement this plan. Steps use checkbox (`- [ ]`) syntax for tracking. **Goal:** [One sentence describing what this builds] **Architecture:** [2-3 sentences about approach] **Tech Stack:** [Key technologies/libraries] ---
### Task N: [Component Name]
**Files:**
- Create: `exact/path/to/file.py`
- Modify: `exact/path/to/existing.py:123-145`
- Test: `tests/exact/path/to/test.py`
- [ ] **Step 1: Write the failing test**
```python
def test_specific_behavior():
result = function(input)
assert result == expectedRun: `pytest tests/path/test.py::test_name -v` Expected: FAIL with "function not defined"
def function(input):
return expectedRun: `pytest tests/path/test.py::test_name -v` Expected: PASS
git add tests/path/test.py src/path/file.py git commit -m "feat: add specific feature"
## Remember - Exact file paths always - Complete code in plan (not "add validation") - Exact commands with expected output - Reference relevant skills with @ syntax - DRY, YAGNI, TDD, frequent commits ## Plan Review Loop After completing each chunk of the plan: 1. Dispatch plan-document-reviewer subagent (see plan-document-reviewer-prompt.md) with precisely crafted review context — never your session history. This keeps the reviewer focused on the plan, not your thought process. - Provide: chunk content, path to spec document 2. If ❌ Issues Found: - Fix the issues in the chunk - Re-dispatch reviewer for that chunk - Repeat until ✅ Approved 3. If ✅ Approved: proceed to next chunk (or execution handoff if last chunk) **Chunk boundaries:** Use `## Chunk N: <name>` headings to delimit chunks. Each chunk should be ≤1000 lines and logically self-contained. **Review loop guidance:** - Same agent that wrote the plan fixes it (preserves context) - If loop exceeds 5 iterations, surface to human for guidance - Reviewers are advisory - explain disagreements if you believe feedback is incorrect ## Execution Handoff After saving the plan: **"Plan complete and saved to `docs/superpowers/plans/<filename>.md`. Ready to execute?"** **Execution path depends on harness capabilities:** **If harness has subagents (Claude Code, etc.):** - **REQUIRED:** Use superpowers:subagent-driven-development - Do NOT offer a choice - subagent-driven is the standard approach - Fresh subagent per task + two-stage review **If harness does NOT have subagents:** - Execute plan in current session using superpowers:executing-plans - Batch execution with checkpoints for review
CoCo Super Intelligence is the orchestration layer that turns Claude Code, Cursor, or Codex into an engineering department: a routed advisory board, 185 skills, 280 commands, persistent state. Local. Open-core — MIT core; Super Intelligence is proprietary, own-use.
Repo: coco-research/coco
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