Install
$ agentstack add skill-jjmartres-opencode-project-docs ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Project Documentation Generator
Generate complete, professional documentation structures for software projects. Automatically adapts content and structure based on project language (Python/Go), context (OpenSource/internal), and existing files.
Core Documentation Files
Always generate these five core files:
- README.md - Project overview, quick start, badges
- ARCHITECTURE.md - System design, components, data flow
- USER_GUIDE.md - Usage examples, configuration, troubleshooting
- DEVELOPER_GUIDE.md - Development setup, testing, contribution workflow
- CONTRIBUTING.md - Contribution guidelines, code standards, PR process
Workflow
1. Context Detection
Before generating docs, detect:
- Language: Scan for
go.mod,pyproject.toml,requirements.txt,setup.py - Project type: Check for
Dockerfile,terraform/,k8s/, AI/ML indicators - Existing docs: Identify what already exists to avoid duplication
- License: Detect from LICENSE file or ask user
- Context: Determine if OpenSource or internal based on repo structure
2. Ask Clarifying Questions
Ask user ONE question at a time to fill gaps:
- "What's the primary purpose of this project in one sentence?"
- "Who's the main audience? (developers, ops, end-users, all)"
- "Is this OpenSource or internal? (affects badges, contact info)"
- "Any company-specific tooling to mention? (Jira, Slack channels, etc.)"
3. Content Adaptation
Read references/templates.md to select appropriate template variants based on detected context.
Language-specific elements:
- Python: Package managers (
uv,pip,poetry), testing (pytest), linting (ruff,mypy) - Go: Build commands, testing,
golangci-lint, module structure
Context-specific elements:
- OpenSource: Badges, CODEOFCONDUCT, security policy, community guidelines
- Internal: Slack channels, internal tools, compliance requirements, team contacts
Project type adjustments:
- AI Agents: MCP architecture, prompt patterns, example interactions
- Infrastructure: Terraform/K8s setup, deployment procedures, DR plans
- Microservices: API schemas, service mesh, health checks
- CLI Tools: Installation methods, command examples, flags
4. File Generation
Generate files in this order:
- README.md first (most visible, sets tone)
- ARCHITECTURE.md (technical foundation)
- DEVELOPER_GUIDE.md (setup and contribution)
- USER_GUIDE.md (end-user focused)
- CONTRIBUTING.md (community guidelines)
Each file must:
- Use clear headers and structure from templates
- Include concrete, runnable examples
- Reference other docs when needed (avoid duplication)
- Match project's actual structure and commands
5. Template Application
For each file:
- Select template variant from
references/templates.md - Fill in project-specific details
- Add context-appropriate sections
- Ensure consistency across all files
6. Quality Checks
Before finalizing, verify:
- All code examples are runnable and accurate
- Commands match detected language/tooling
- Cross-references between docs are correct
- No placeholder text remains
- Tone is consistent (technical/friendly/formal based on context)
7. Output
Place all files in docs/ and use present_files to share with user.
Resources
references/templates.md
Contains complete documentation templates for all five core files with variants for:
- Python vs Go projects
- OpenSource vs internal contexts
- Different project types (agent, service, CLI, infra)
- Different complexity levels
Claude should read this file to select appropriate templates before generating docs.
Special Considerations
For AI Agent projects:
- Explain MCP server architecture
- Document tool integrations
- Show example prompts and interactions
- Include LLM configuration details
For Infrastructure/DevOps:
- Environment requirements (cloud providers, versions)
- Deployment runbooks
- Monitoring setup
- Disaster recovery procedures
For Microservices:
- API endpoint documentation
- Service dependency diagrams
- Inter-service communication patterns
- Health check and metrics endpoints
Quality Standards
Every documentation file must:
- Have table of contents for files >200 lines
- Use proper code fences with language tags
- Include "Quick Start" section at top
- Show real, tested examples
- Explain "why" decisions were made
- Use consistent terminology throughout
Avoid
- Generic placeholder text like "TODO" or "Coming soon"
- Outdated technology references
- Overly complex explanations without examples
- Duplicating content across multiple files
- Missing concrete code examples
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: jjmartres
- Source: jjmartres/opencode
- License: MIT
Install and usage instructions live in the source repository linked above.
Reviews
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Versions
- v0.1.0 Imported from the upstream source.