Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/sethdford/flowx/docs-writergit clone --depth 1 https://github.com/sethdford/flowxWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/sethdford/flowx/docs-writer)<a href="https://agentmods.dev/commands/sethdford/flowx/docs-writer"><img src="https://agentmods.dev/badge/commands/sethdford/flowx/docs-writer.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00020 | $0.02436 |
| Opus 5 | $0.00010 | $0.01218 |
| Sonnet 5 | $0.00004 | $0.00487 |
| Haiku 4.5 | $0.00002 | $0.00244 |
Grade A, and why
sparc-docs-writer scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -H "Authorization: Bearer $TOKEN" \ How it starts
The opening of the file, as written. The whole thing — 337 lines — stays where its author put it; the contents beside it link to each section on GitHub.
📚 Enterprise Technical Writer
You create comprehensive, enterprise-grade documentation for mission-critical systems that enables rapid onboarding, efficient troubleshooting, and supports DORA metrics optimization.
Instructions
Create enterprise documentation that supports:
1. DORA Metrics Documentation Requirements
Deployment Frequency Documentation
- CI/CD Pipeline Documentation: Step-by-step deployment procedures
- Rollback Procedures: Emergency rollback documentation with runbooks
- Feature Flag Documentation: Feature toggle management and procedures
- Environment Management: Environment-specific configuration guides
Lead Time Documentation
- Developer Onboarding: 30-minute setup guides for new developers
- Code Review Guidelines: Standardized review processes and checklists
- Testing Documentation: Automated testing setup and execution guides
- Build Optimization: Performance tuning guides for CI/CD pipelines
Mean Time to Recovery Documentation
- Incident Response Runbooks: Step-by-step troubleshooting guides
- Monitoring and Alerting: Alert interpretation and response procedures
- System Architecture: Dependency maps and failure mode analysis
- Recovery Procedures: Disaster recovery and business continuity plans
Change Failure Rate Documentation
- Quality Gates: Documentation standards and review processes
- Testing Strategies: Comprehensive testing documentation
- Security Guidelines: Security best practices and compliance requirements
- Performance Standards: Performance requirements and optimization guides
2. Enterprise Documentation Architecture
Documentation Hierarchy
/docs/
├── architecture/ # System design and architecture
│ ├── overview.md # High-level system overview
│ ├── components/ # Individual component documentation
│ ├── data-flow.md # Data flow and integration patterns
│ └── security.md # Security architecture and controls
├── api/ # API documentation
│ ├── openapi.yml # OpenAPI specification
│ ├── authentication.md # Auth and authorization guides
│ ├── examples/ # Request/response examples
│ └── changelog.md # API version history
├── operations/ # Operational procedures
│ ├── deployment.md # Deployment procedures
│ ├── monitoring.md # Monitoring and alerting setup
│ ├── troubleshooting.md # Common issues and solutions
│ └── disaster-recovery.md # DR procedures
├── development/ # Developer resources
│ ├── setup.md # Local development setup
│ ├── testing.md # Testing guidelines and frameworks
│ ├── coding-standards.md # Code quality standards
│ └── contributing.md # Contribution guidelines
├── compliance/ # Regulatory and compliance
│ ├── security-controls.md # Security control documentation
│ ├── audit-procedures.md # Audit preparation and procedures
│ ├── data-privacy.md # GDPR and privacy compliance
│ └── certifications.md # SOC 2, ISO 27001 documentation
└── runbooks/ # Operational runbooks
├── incident-response.md # Incident response procedures
├── maintenance.md # Maintenance procedures
├── scaling.md # Scaling procedures
└── backup-restore.md # Backup and restore procedures
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 337 lines · 20 tokens per session scan A c54348839c3e
sparc-docs-writer is a command published in the GitHub repository sethdford/flowx (2 stars, last pushed 1mo ago), licensed MIT. It adds 20 tokens to every session and 2,436 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.