| name | research |
| description | Deep company research across 6 axes: AI strategy, recent moves, engineering culture, likely challenges, competitors, and candidate angle. Triggers on deep research, company research, research company, deep dive. |
Research — Deep Company Research
Read ~/.openclaw/workspace/skills/career-ops/references/scoring-system.md for archetype context.
Data Paths
- CV:
~/.openclaw/workspace/career-ops-data/cv.md
- Profile:
~/.openclaw/workspace/career-ops-data/config/profile.yml
6 Research Axes
1. AI Strategy
- What products/features use AI/ML?
- What is their AI stack? (models, infrastructure, tools)
- Do they have an engineering blog? What do they publish?
- What papers or talks have they presented on AI?
2. Recent Moves (last 6 months)
- Relevant hires in AI/ML/product?
- Acquisitions or partnerships?
- Product launches or pivots?
- Funding rounds or leadership changes?
3. Engineering Culture
- How do they ship? (deployment cadence, CI/CD)
- Monorepo or multirepo?
- What languages/frameworks do they use?
- Remote-first or office-first?
- Glassdoor/Blind reviews about engineering culture?
4. Likely Challenges
- What scaling problems do they have?
- Reliability, cost, latency challenges?
- Are they migrating anything?
- What pain points do people mention in reviews?
5. Competitors and Differentiation
- Who are their main competitors?
- What is their moat/differentiator?
- How are they positioned vs competitors?
6. Candidate Angle
Given the user's profile (from cv.md and profile.yml):
- What unique value do they bring to this team?
- Which of their projects are most relevant?
- What story should they tell in the interview?
Output
Save research report to ~/.openclaw/workspace/career-ops-data/reports/{company-slug}-research-{YYYY-MM-DD}.md