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Research and analyze feature viability - GO/NO-GO decision gate

Install / Use

npx skills add shanraisshan/claude-code-best-practice

Installs into whichever agent you are using.

About this skill
⚡

Claude Commands

Claude Code slash commands

Quality Score

94/100

Supported Platforms

Claude Code

Tags

Our assessment of research

research scores 94/100 on our quality scale, 17th of 127 Education & Research skills we index (top 14%).

Its Claude Commands is 12 KB long, well organised into 20 sections with 1 code example: a thorough specification that gives an agent plenty to work with.

With 66,294 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
30/30
Structure
17/20
Description
12/15
Adoption
20/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated yesterday, so research is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.

AI review by kimi-k2.7-code on 2026-09-25. Automated pattern scan on 2026-09-25. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

research compared with similar skills

All 4 of these similar skills score higher than research; compare them before choosing.

SkillScoreStarsUpdatedFormat
research (this skill)by shanraisshan9466.3k1d agoClaude Commands
claude-memby thedotmack10094.7ktodayCLAUDE.md
Agent-Reachby Panniantong10085.4k10d agoCLAUDE.md
Understand-Anythingby Egonex-AI10084.2k13d agoCLAUDE.md
headroomby headroomlabs-ai10073.8ktodayCLAUDE.md

Frequently asked questions

How do I install research?
Run npx skills add shanraisshan/claude-code-best-practice. The install tabs above show the steps for each supported agent.
Which AI agents does research work with?
It is written for Claude Code, as a Claude Commands file. Other agents that read the same format can often use it too.
Is research safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is research still maintained?
The repository was last updated yesterday, so research is actively maintained.

description: Research and analyze feature viability - GO/NO-GO decision gate argument-hint: "<feature-slug>"

User Input

$ARGUMENTS

You MUST parse the user input to extract the feature slug (the folder name in rpi/).

Expected Input Format: rpi/{feature-slug}/REQUEST.md

Purpose

This command performs comprehensive research and analysis of feature requests before the planning phase begins. It acts as a critical GO/NO-GO gate to determine whether a feature idea should proceed to detailed planning.

Key Objectives:

  • Assess product-market fit and user value
  • Evaluate technical feasibility and complexity
  • Identify risks and potential blockers
  • Determine the right approach (build, buy, partner, or decline)
  • Make go/no-go recommendation with clear rationale

Prerequisites:

  • Feature folder exists at rpi/{feature-slug}/
  • Feature request file exists at rpi/{feature-slug}/REQUEST.md

Output Location: rpi/{feature-slug}/research/RESEARCH.md

This is Step 2 of the RPI Workflow (after initial feature description in Step 1).

Outline

  1. Load Context: Read feature description from rpi/{feature-slug}/ and project constitution (if exists)
  2. Parse Feature Request: Use requirement-parser agent to extract structured requirements
  3. Execute Multi-Phase Research:
    • Phase 1: Parse Feature Request (requirement-parser agent)
    • Phase 2: Product Analysis with Constitution Alignment (product-manager agent)
    • Phase 2.5: Technical Discovery (Explore agent) - CRITICAL: Deep code exploration
    • Phase 3: Technical Feasibility (senior-software-engineer agent)
    • Phase 4: Strategic Assessment (technical-cto-advisor agent)
    • Phase 5: Generate Research Report (documentation-analyst-writer agent)
  4. Synthesize Recommendation: Combine all analyses into clear go/no-go recommendation
  5. Validate Output: Check against quality gates
  6. Report Completion: Provide recommendation, next steps, and report location

Phases

Phase 0: Load Context

Prerequisites: Feature slug provided, rpi/{feature-slug}/REQUEST.md exists

Process:

  1. Read feature description:

    • Read rpi/{feature-slug}/REQUEST.md (required)
    • Extract feature requirements and goals from REQUEST.md
  2. Check for project constitution (optional):

    • Look for a constitution or principles document in the repository
    • Common locations: constitution.md, PRINCIPLES.md, .project/constitution.md
    • If found, extract core principles, constraints, and objectives
  3. Create research context:

    • Synthesize into concise summary for agents
    • Identify key alignment criteria

Outputs:

  • Feature description summary
  • Constitutional principles (if found)
  • Alignment criteria for evaluation

Validation:

  • [ ] Feature folder exists in rpi/{feature-slug}/
  • [ ] Feature description extracted
  • [ ] Constitution checked and loaded (if exists)

Phase 1: Parse Feature Request

Prerequisites: Phase 0 complete

Agent: requirement-parser (planning domain)

Process:

  1. Launch requirement-parser agent with feature description

  2. Agent extracts:

    • Feature name and type
    • Target component(s)
    • Goals and objectives
    • Functional and non-functional requirements
    • Constraints and assumptions
    • Complexity estimate
    • Clarifying questions (if any)
  3. Review parsing results:

    • If clarifying questions exist, STOP and ask user before proceeding

Outputs:

  • Structured requirements document
  • Feature metadata (name, type, component, complexity)
  • Clarifying questions (if any)

Phase 2: Product Analysis with Constitution Alignment

Prerequisites: Phase 1 complete, requirements clear

Agent: product-manager

Process:

  1. Launch product-manager agent with:

    • Parsed requirements from Phase 1
    • Constitutional context from Phase 0
  2. Agent analyzes:

    • User Value: Who benefits? How much impact?
    • Market Fit: Does this align with market needs?
    • Product Vision: Does this fit our product strategy?
    • Constitutional Alignment: Does this align with project principles?
    • Constraints Check: Does this violate any constitutional constraints?
  3. Agent provides:

    • Product viability score (High/Medium/Low)
    • User value assessment
    • Strategic alignment evaluation
    • Priority recommendation
    • Product concerns or red flags

Outputs:

  • Product viability assessment
  • User value analysis
  • Strategic alignment score
  • Constitutional alignment summary (if applicable)

Phase 2.5: Technical Discovery (Code Exploration)

Prerequisites: Phases 1-2 complete, product viability established

Agent: Explore (via Task tool with subagent_type="Explore")

Purpose: CRITICAL PHASE - Deeply analyze existing codebase BEFORE making technical feasibility assessment.

Process:

  1. Launch Explore agent with target component(s)

  2. Agent investigates:

    • Existing Implementation: What code already exists for similar functionality?
    • Integration Points: What systems/modules would this feature touch?
    • Current Architecture: How is the current system structured?
    • Data Models: What database schemas or data structures exist?
    • Dependencies: What libraries, services are already integrated?
    • Existing Patterns: What coding patterns and conventions are used?
  3. Agent provides:

    • Current State Summary: What exists today
    • Integration Analysis: Where proposed feature would fit
    • Code Conflicts: What would break or conflict
    • Leverage Opportunities: What can be reused vs rebuilt
    • Technical Constraints: Real constraints from existing code

Outputs:

  • Current implementation summary
  • Integration points map
  • Code conflicts identified
  • Reusable components identified
  • Technical constraints from code

Critical: This phase ensures Phase 3 is based on actual code reality, not assumptions.


Phase 3: Technical Feasibility Assessment

Prerequisites: Phases 1-2.5 complete, code explored

Agent: senior-software-engineer

Process:

  1. Launch senior-software-engineer agent with:

    • Parsed requirements from Phase 1
    • Product context from Phase 2
    • Technical discovery results from Phase 2.5
  2. Agent analyzes (informed by Phase 2.5 discoveries):

    • Technical Approach: What are the implementation options?
    • Complexity: How difficult is this to build?
    • Dependencies: What systems/services are needed?
    • Technical Debt: Will this create or reduce tech debt?
    • Risks: What are the technical risks?
  3. Agent provides:

    • Technical feasibility score (High/Medium/Low)
    • Recommended approach (with alternatives)
    • Complexity estimate (Simple/Medium/Complex)
    • Technical risks and mitigations

Outputs:

  • Technical feasibility score
  • Recommended implementation approach
  • Complexity and effort estimate
  • Technical risks and mitigations

Phase 4: Strategic Assessment

Prerequisites: Phases 1-3 complete

Agent: technical-cto-advisor

Process:

  1. Launch technical-cto-advisor agent with all previous phase outputs

  2. Agent synthesizes:

    • Overall Assessment: Combine product + technical perspectives
    • Strategic Alignment: Does this align with engineering principles AND project constitution?
    • Risk vs. Reward: Is the value worth the effort and risk?
    • Alternative Options: Build, buy, partner, defer, or decline?
  3. Agent provides:

    • Go/No-Go Recommendation: Clear decision with confidence level
    • Rationale: Detailed reasoning
    • Recommended Approach: If "go", what's the best path forward?
    • Conditions: Any prerequisites for proceeding?
    • Risks: Key risks if we proceed

Outputs:

  • Go/No-Go recommendation
  • Strategic rationale
  • Recommended approach
  • Risk summary

Phase 5: Generate Research Report

Prerequisites: Phases 1-4 complete

Agent: documentation-analyst-writer (via Task tool)

Process:

  1. Launch documentation-analyst-writer agent with all phase outputs

  2. Agent generates report with sections:

    • Executive Summary: One-paragraph overview with recommendation
    • Feature Overview: Name, type, component, goals
    • Requirements Summary: Key functional and non-functional requirements
    • Product Analysis: User value, market fit, strategic alignment
    • Technical Discovery: Current state, integration points, constraints from code
    • Technical Analysis: Feasibility, approach, complexity, risks
    • Strategic Recommendation: Go/no-go with detailed rationale
    • Next Steps: What to do based on recommendation
  3. Agent creates markdown file: rpi/{feature-slug}/research/RESEARCH.md

Outputs:

  • Complete research report saved to rpi/{feature-slug}/research/RESEARCH.md

Sub-Agent Delegation

This command orchestrates 6 specialist agents:

| Phase | Agent | Type | Location | |-------|-------|------|----------| | Phase 1 | requirement-parser | Custom | .claude/agents/requirement-parser.md | | Phase 2 | product-manager | Custom | .claude/agents/product-manager.md | | Phase 2.5 | Explore | Built-in | Task tool with subagent_type="Explore" | | Phase 3 | senior-software-engineer | Custom | .claude/agents/senior-software-engineer.md | | Phase 4 | technical-cto-advisor | Custom | .claude/agents/technical-cto-advisor.md | | Phase 5 | documentation-analyst-writer | Built-in | Task tool with subagent_type="documentation-analyst-writer" |


Completion Report

Report the following on successful completion:

Research Recommendation

Decision: [GO | NO-GO | CONDITIONAL GO | DEFER]

Confidence: [High | Medium | Low]

Rationale (1-2 sentences): [Key reasons for recommendation]


Research Summary

Feature: {feature-name} Type: {feature-type} Component: {target-component} Complexity: {Simple | Medium | Complex}

Scores:

  • Product Viability: [High/Medium/Low]
  • Technical Feasibility: [High/Medium/Low]
  • Overall Assessment: [High/Medium/Low]

Key Risks:

  1. {risk-1}
  2. {risk-2}
  3. {risk-3}

Report Location

Full Research Report: rpi/{feature-slug}/research/RESEARCH.md


Next Steps

Based on the [GO/NO-GO] recommendation:

If GO:

  1. Review the research report: rpi/{feature-slug}/research/RESEARCH.md
  2. Proceed to planning: /rpi:plan "{feature-slug}"

If CONDITIONAL GO:

  1. Review conditions in report
  2. Address conditions before proceeding
  3. Re-run research if needed

If DEFER:

  1. Review timeline recommendation in report
  2. Revisit when timing is appropriate

If NO-GO:

  1. Review rationale in report
  2. Consider alternatives mentioned
  3. Archive for future reference

Error Handling

If REQUEST.md doesn't exist:

  • Action: Stop and inform user
  • Message: "Feature request file rpi/{feature-slug}/REQUEST.md not found. Create the feature folder and REQUEST.md first (Step 1: Describe in Plan Mode)."

If feature description is too vague:

  • Action: requirement-parser will identify clarifying questions
  • Message: "Need more information. Please answer:"
  • Next: Wait for answers, then proceed

If agents fail or timeout:

  • Action: Retry once
  • Next: If retry fails, ask user whether to continue with incomplete research

Notes

  • When to Use: After Step 1 (Describe) creates the feature folder
  • Critical Gate: This prevents wasted effort on non-viable features
  • Part of RPI Workflow: Step 2 of 4 (Describe → Research → Plan → Implement)

Post-Completion Action

IMPORTANT: After completing the research workflow, ALWAYS prompt the user to compact the conversation:

Context Management: This research workflow consumed significant context. T

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars66.3k
CategoryEducation
Updated1d ago
Forks6.6k

Languages

HTML

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions