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 want phase research without planning: to investigate before deciding a phase is feasible, or to re-research after a plan already exists. Standalone command; most workflows should use /gsd-plan-phase instead.
$ npx -y skills add coco-research/coco --skill gsd-research-phase --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/gsd-research-phaseContext preview
The summary Claude sees to decide when to auto-load this skill.
Use when you want phase research without planning: to investigate before deciding a phase is feasible, or to re-research after a plan already exists. Standalone command; most workflows should use /gsd-plan-phase instead.
name: gsd-research-phase description: "Use when you want phase research without planning: to investigate before deciding a phase is feasible, or to re-research after a plan already exists. Standalone command; most workflows should use /gsd-plan-phase instead." argument-hint: "[phase]" allowed-tools: - Read - Bash - Task
<objective> Research how to implement a phase. Spawns gsd-phase-researcher agent with phase context.
**Note:** This is a standalone research command. For most workflows, use `/gsd-plan-phase` which integrates research automatically.
**Use this command when:**
**Orchestrator role:** Parse phase, validate against roadmap, check existing research, gather context, spawn researcher agent, present results.
**Why subagent:** Research burns context fast (WebSearch, Context7 queries, source verification). Fresh 200k context for investigation. Main context stays lean for user interaction. </objective>
<available_agent_types> Valid GSD subagent types (use exact names — do not fall back to 'general-purpose'):
</available_agent_types>
<context> Phase number: $ARGUMENTS (required)
Normalize phase input in step 1 before any directory lookups. </context>
<process>
INIT=$(node "$HOME/.claude/get-shit-done/bin/gsd-tools.cjs" init phase-op "$ARGUMENTS")
if [[ "$INIT" == @file:* ]]; then INIT=$(cat "${INIT#@file:}"); fiExtract from init JSON: `phase_dir`, `phase_number`, `phase_name`, `phase_found`, `commit_docs`, `has_research`, `state_path`, `requirements_path`, `context_path`, `research_path`.
Resolve researcher model:
RESEARCHER_MODEL=$(node "$HOME/.claude/get-shit-done/bin/gsd-tools.cjs" resolve-model gsd-phase-researcher --raw)
PHASE_INFO=$(node "$HOME/.claude/get-shit-done/bin/gsd-tools.cjs" roadmap get-phase "${phase_number}")**If `found` is false:** Error and exit. **If `found` is true:** Extract `phase_number`, `phase_name`, `goal` from JSON.
ls .planning/phases/${PHASE}-*/RESEARCH.md 2>/dev/null**If exists:** Offer: 1) Update research, 2) View existing, 3) Skip. Wait for response.
**If doesn't exist:** Continue.
Use paths from INIT (do not inline file contents in orchestrator context):
Present summary with phase description and what files the researcher will load.
Research modes: ecosystem (default), feasibility, implementation, comparison.
<research_type>
Phase Research — investigating HOW to implement a specific phase well.
</research_type>
<key_insight>
The question is NOT "which library should I use?"
The question is: "What do I not know that I don't know?"
For this phase, discover:
- What's the established architecture pattern?
- What libraries form the standard stack?
- What problems do people commonly hit?
- What's SOTA vs what Claude's training thinks is SOTA?
- What should NOT be hand-rolled?
</key_insight>
<objective>
Research implementation approach for Phase {phase_number}: {phase_name}
Mode: ecosystem
</objective>
<files_to_read>
- {requirements_path} (Requirements)
- {context_path} (Phase context from discuss-phase, if exists)
- {state_path} (Prior project decisions and blockers)
</files_to_read>
<additional_context>
**Phase description:** {phase_description}
</additional_context>
<downstream_consumer>
Your RESEARCH.md will be loaded by `/gsd-plan-phase` which uses specific sections:
- `## Standard Stack` → Plans use these libraries
- `## Architecture Patterns` → Task structure follows these
- `## Don't Hand-Roll` → Tasks NEVER build custom solutions for listed problems
- `## Common Pitfalls` → Verification steps check for these
- `## Code Examples` → Task actions reference these patterns
Be prescriptive, not exploratory. "Use X" not "Consider X or Y."
</downstream_consumer>
<quality_gate>
Before declaring complete, verify:
- [ ] All domains investigated (not just some)
- [ ] Negative claims verified with official docs
- [ ] Multiple sources for critical claims
- [ ] Confidence levels assigned honestly
- [ ] Section names match what plan-phase expects
</quality_gate>
<output>
Write to: .planning/phases/${PHASE}-{slug}/${PHASE}-RESEARCH.md
</output>Task(
prompt=filled_prompt,
subagent_type="gsd-phase-researcher",
model="{researcher_model}",
description="Research Phase {phase}"
)**`## RESEARCH COMPLETE`:** Display summary, offer: Plan phase, Dig deeper, Review full, Done.
**`## CHECKPOINT REACHED`:** Present to user, get response, spawn continuation.
**`## RESEARCH INCONCLUSIVE`:** Show what was attempted, offer: Add context, Try different mode, Manual.
<objective>
Continue research for Phase {phase_number}: {phase_name}
</objective>
<prior_state>
<files_to_read>
- .planning/phases/${PHASE}-{slug}/${PHASE}-RESEARCH.md (Existing research)
</files_to_read>
</prior_state>
<checkpoint_response>
**Type:** {checkpoint_type}
**Response:** {user_response}
</checkpoint_response>Task(
prompt=continuation_prompt,
subagent_type="gsd-phase-researcher",
model="{researcher_model}",
description="Continue research Phase {phase}"
)</process>
<success_criteria>
</success_criteria>
CoCo Super Intelligence is the orchestration layer that turns Claude Code, Cursor, or Codex into an engineering department: a routed advisory board, 226 skills, 386 commands, persistent state. Local. Open-core — MIT core; Super Intelligence is proprietary, own-use.
Repo: coco-research/coco
Create Cursor rules for persistent AI guidance. Use when the user wants to create a rule, add coding standards, set up project conventions, configure…
Guides users through creating effective Agent Skills for Cursor. Use when the user wants to create, write, or author a new skill, or asks about skill…
Create custom subagents for specialized AI tasks. Use when the user wants to create a new type of subagent, set up task-specific agents, configure code…
Convert 'Applied intelligently' Cursor rules (.cursor/rules/*.mdc) and slash commands (.cursor/commands/*.md) to Agent Skills format (.cursor/skills/). Use…
Modify Cursor/VSCode user settings in settings.json. Use when the user wants to change editor settings, preferences, configuration, themes, font size, tab…
Train and optimize AI agents using Microsoft's Agent Lightning framework with reinforcement learning. Use when setting up agent training, instrumenting agents…