research

name	research
description	Use for Phase 1 of the development workflow: AI deep research. Ingests human research materials from workflow/research/manual/ and performs web search, codebase analysis, and cross-referencing to produce a comprehensive research synthesis. Use when someone says 'start research', 'phase 1', 'research phase', 'deep research', or has placed materials in workflow/research/manual/.

What This Skill Does

Executes Phase 1 (Research & Discovery) of the AI-Assisted Development Workflow.

Prerequisites

Human has placed research materials in workflow/research/manual/. Materials can be any format: markdown, PDF, URLs, images, conversations, git repos, API specs, stakeholder notes, competitor examples, screenshots, etc.

Important

If workflow/research/final/research.md already exists but workflow/research/final/rfc.md does not, the phase was run before the review process was added. Create the RFC file now and ask the human to review before proceeding.

Prompt

CONTEXT:

• Project: {{PROJECT_NAME}}
• Description: {{ONE_LINE_DESCRIPTION}}
• Business Objective: {{WHAT_PROBLEM_ARE_WE_SOLVING}}
• Target Users: {{WHO_WILL_USE_THIS}}
• Budget/Timeline Constraints: {{ANY_KNOWN_CONSTRAINTS}}

RESEARCH INPUTS:

Read all files in workflow/research/manual/. These are materials gathered during human manual research and may include business objectives, high-level design intent (UI, UX, architecture), external references, API docs, competitor analysis, stakeholder conversations, and constraints.

{{LIST_ANY_ADDITIONAL_URLS_OR_RESOURCES_TO_RESEARCH}}

If a project instruction file exists (CLAUDE.md or .github/copilot-instructions.md), read it for existing tooling preferences, version constraints, or coding standards. Treat these as project constraints.

ROLE:

If executing research, activate the software-architect agent by default. For highly domain-specific projects, activate the domain-specialist agent instead.

INSTRUCTIONS:

You are performing deep research to complement the human's manual research. Do not merely summarize — add value by:

1. Cross-reference the manual research materials against each other. Identify contradictions, gaps, and unstated assumptions.
2. Expand coverage through web search, codebase analysis, and exploration of adjacent patterns. Look for:
   • Alternative architectures or approaches the human may not have considered
   • Edge cases, rate limits, scaling considerations for referenced APIs/services
   • Competing products and how they solve similar problems
   • Known pitfalls with the technologies or patterns mentioned in the manual research
3. Synthesize everything (human findings + your findings) into a unified research document.

Produce the output with these sections:

1. Business Requirements — What the system must do, prioritized (must-have vs nice-to-have).
2. Technical Constraints — Budget, timeline, tech stack requirements, compliance, deployment targets, team skills.
3. Reference Architectures — Similar systems that exist, patterns they use, lessons learned.
4. External Dependencies — Third-party APIs, services, or data sources to integrate with. Include auth methods, rate limits, and pricing where known.
5. AI Research Additions — Findings from your own research that were not present in the manual materials. Clearly distinguish what is new.
6. Open Questions — Things we still need to resolve before designing. Flag anything ambiguous or contradictory.
7. Recommended Tech Stack — With brief justification for each choice.
8. Inaccessible Resources — Any URLs or resources you could not access (blocked by bot protection, auth-walled, paywalled, etc.). For each, state what the resource was and why you couldn't access it, so the human can manually provide the content.

OUTPUT FORMAT:

Save as workflow/research/final/research.md. Place any processed reference materials in workflow/research/final/references/. Use headings, bullet points, and tables. Keep it scannable — no prose paragraphs.

Also update the Overview section of README.md with a concise problem statement and project description based on the research findings.

CONSTRAINTS:

• Do NOT make architecture decisions. This is research, not design.
• If information is missing, list it under "Open Questions" rather than guessing.
• Cite sources where possible.
• If you cannot access a URL or resource, list it under "Inaccessible Resources" with an explanation. NEVER silently skip a resource.
• Link to detailed references rather than inlining large content.
• When recommending technologies, libraries, or runtimes, always recommend the current stable or LTS version — never an EOL or near-EOL version. If the manual research specifies a version, note whether it is still supported and flag if it is outdated.
• If your tech stack recommendation involves a non-obvious choice between 2+ viable options, create a decision record in workflow/decisions/DR-NNN-title.md and update workflow/decisions/README.md. Structure the record with: Phase, Date, Status, Context, Options Considered, Decision, and Consequences. Do NOT create records for trivial choices.

HUMAN REVIEW PROCESS:

After you produce workflow/research/final/research.md, create workflow/research/final/rfc.md with a brief summary of key findings and any areas where you had low confidence.

Then STOP and ask the human to review. Do NOT proceed to the next phase or suggest next steps.

The human will review research.md and may add *FEEDBACK:* comments in the review file.

• Respond with *AI:* comments explaining what was changed and why, then update research.md accordingly.
• Do not overwrite previous discussion — append new responses below existing conversation.
• The phase is complete only when the human explicitly approves. Do NOT move to Phase 2 until told.