openviking▌
volcengine/openviking · updated Apr 8, 2026
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IMPORTANT: All ov commands are terminal (shell) commands — run them via the bash tool. Execute directly — no pre-checks, no test commands. Handle errors when they occur.
OpenViking Code Repository Search
IMPORTANT: All ov commands are terminal (shell) commands — run them via the bash tool. Execute directly — no pre-checks, no test commands. Handle errors when they occur.
How OpenViking Organizes Data
OpenViking stores content in a virtual filesystem under the viking:// namespace. Each URI maps to a file or directory, e.g. viking://resources/fastapi/routing.py. Each directory has AI-generated summaries (abstract / overview). The key principle: narrow the URI scope to improve retrieval efficiency. Instead of searching all repos, lock to a specific repo or subdirectory — this reduces noise and speeds up results significantly.
Search Commands
Choose the right command based on what you're looking for:
| Command | Use when | Example |
|---|---|---|
ov search |
Semantic search — use for concept/intent based queries | "dependency injection", "how auth works" |
ov grep |
You know the exact keyword or symbol | function name, class name, error string |
ov glob |
You want to enumerate files by pattern | all *.py files, all test files |
# Semantic search
ov search "dependency injection" --uri viking://resources/fastapi --limit 10
ov search "how tokens are refreshed" --uri viking://resources/fastapi/fastapi/security
ov search "JWT authentication" --limit 10 # across all repos
ov search "error handling" --limit 5 --threshold 0.7 # filter low-relevance results
# Keyword search — exact match or regex
ov grep "verify_token" --uri viking://resources/fastapi
ov grep "class.*Session" --uri viking://resources/requests/requests
# File enumeration — by name pattern (always specify --uri to scope the search)
ov glob "**/*.py" --uri viking://resources/fastapi
ov glob "**/test_*.py" --uri viking://resources/fastapi/tests
ov glob "**/*.py" --uri viking://resources/ # across all repos
Narrowing scope: once you identify a relevant directory, pass it as --uri to restrict subsequent searches to that subtree — this is faster and more precise than searching the whole repo.
Query formulation: write specific, contextual queries rather than single keywords.
ov search "API" # too vague
ov search "REST API authentication with JWT tokens" # better
ov search "JWT token refresh flow" --uri viking://resources/backend # best
Read Content
# Directories: AI-generated summaries
ov abstract viking://resources/fastapi/fastapi/dependencies/ # one-line summary
ov overview viking://resources/fastapi/fastapi/dependencies/ # detailed breakdown
# Files: raw content
ov read viking://resources/fastapi/fastapi/dependencies/utils.py
ov read viking://resources/fastapi/fastapi/dependencies/utils.py --offset 100 --limit 50
abstract / overview only work on directories. read only works on files.
Browse
ov ls viking://resources/ # list all indexed repos
ov ls viking://resources/fastapi # list repo top-level contents
ov ls viking://resources/fastapi --simple # paths only, no metadata
ov ls viking://resources/fastapi --recursive # list all files recursively
ov tree viking://resources/fastapi # full directory tree (default: 3 levels deep)
ov tree viking://resources/fastapi -L 2 # limit depth to 2 levels
ov tree viking://resources/fastapi -l 200 # truncate abstract column to 200 chars
ov tree viking://resources/fastapi -L 2 -l 200 # combined: 2 levels deep, 200-char summaries
-L controls how many levels deep the tree expands. -l controls the length of the AI-generated summary per directory. Use ov tree -L 2 -l 200 as a good starting point to understand a repo's structure before diving in.
Add a Repository
ov add-resource https://github.com/owner/repo --to viking://resources/repo --timeout 300
--timeout is required (seconds). Use 300 (5 min) for small repos, increase for larger ones.
After submitting, run ov observer queue once and report status to user. Indexing runs in background — do not poll or wait.
| Repo Size | Files | Est. Time |
|---|---|---|
| Small | < 100 | 2–5 min |
| Medium | 100–500 | 5–20 min |
| Large | 500+ | 20–60+ min |
Remove a Repository
ov rm viking://resources/fastapi --recursive
This permanently deletes the repo and all its indexed content. Confirm with the user before running.
Error Handling
command not found: ov → Tell user: pip install openviking --upgrade. Stop.
url is required / CLI_CONFIG error → Auto-create config and retry:
mkdir -p ~/.openviking && echo '{"url": "http://localhost:1933"}' > ~/.openviking/ovcli.conf
CONNECTION_ERROR / failed to connect:
~/.openviking/ov.confexists → auto-start server, wait until healthy, retry:openviking-server > /tmp/openviking.log 2>&1 & for i in $(seq 1 10); do ov health 2>/dev/null && break; sleep 3; done- Does not exist → Tell user to configure
~/.openviking/ov.conffirst. Stop.
More Help
For other issues or command details, run:
ov help
ov <command> --help # e.g. ov search --help
How to use openviking on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add openviking
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches openviking from GitHub repository volcengine/openviking and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate openviking. Access the skill through slash commands (e.g., /openviking) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.8★★★★★58 reviews- ★★★★★Omar Tandon· Dec 20, 2024
Keeps context tight: openviking is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Diego Ndlovu· Dec 20, 2024
openviking is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Soo Thompson· Dec 16, 2024
openviking fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Shikha Mishra· Dec 12, 2024
We added openviking from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Kaira Kim· Dec 8, 2024
Solid pick for teams standardizing on skills: openviking is focused, and the summary matches what you get after install.
- ★★★★★Sofia Abebe· Dec 4, 2024
I recommend openviking for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Noor Wang· Dec 4, 2024
openviking fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Kaira Ramirez· Nov 27, 2024
openviking has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Neel Gupta· Nov 23, 2024
openviking is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Diego Shah· Nov 11, 2024
openviking fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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