gsd:research-phase
SkillDev toolsResearch specific phase implementation details
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the gsd:research-phase skill
What this skill tells your AI
The instructions your AI receives, as published by allgpt-co/quickvoice in .claude/skills/gsd/commands/research-phase/SKILL.md and read by ahel’s review.
Note: This is a standalone research command. For most workflows, use /gsd-plan-phase which integrates research automatically.
Use this command when:
- You want to research without planning yet
- You want to re-research after planning is complete
- You need to investigate before deciding if a phase is feasible
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.
<available_agent_types> Valid GSD subagent types (use exact names — do not fall back to 'general-purpose'):
- gsd-phase-researcher — Researches technical approaches for a phase </available_agent_types>
Normalize phase input in step 1 before any directory lookups.
0. Initialize Context
INIT=$(node "$HOME/.claude/get-shit-done/bin/gsd-tools.cjs" init phase-op "$ARGUMENTS")
if [[ "$INIT" == @file:* ]]; then INIT=$(cat "${INIT#@file:}"); fi
Extract 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)
1. Validate Phase
PHASE_INFO=$(node "$HOME/.claude/get-shit-done/bin/gsd-tools.cjs" roadmap get-phase "${phase_number}")
If found is false: Error and exit. If found is true: Extract phase_number, phase_name, goal from JSON.
2. Check Existing Research
ls .planning/phases/${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.
3. Gather Phase Context
Use paths from INIT (do not inline file contents in orchestrator context):
requirements_pathcontext_pathstate_path
Present summary with phase description and what files the researcher will load.
4. Spawn gsd-phase-researcher Agent
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}"
)
5. Handle Agent Return
## 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.
6. Spawn Continuation Agent
<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}"
)
<success_criteria>
- Phase validated against roadmap
- Existing research checked
- gsd-phase-researcher spawned with context
- Checkpoints handled correctly
- User knows next steps </success_criteria>
Signals
- GitHub stars
- 489
- Forks
- 546
- Last commit
- Sep 2026
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gsd-research-phase- Source
- github.com/allgpt-co/quickvoice