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 skills add saolalab/clawforce --skill infrastructuregit clone --depth 1 https://github.com/saolalab/clawforceWrote 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/skills/saolalab/clawforce/infrastructure)<a href="https://agentmods.dev/skills/saolalab/clawforce/infrastructure"><img src="https://agentmods.dev/badge/skills/saolalab/clawforce/infrastructure/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/saolalab/clawforce/infrastructure"><img src="https://agentmods.dev/badge/skills/saolalab/clawforce/infrastructure.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00033 | $0.01318 |
| Opus 5.5 | $0.00013 | $0.00527 |
| Sonnet 5.5 | $0.00007 | $0.00264 |
| Haiku 4.5 | $0.00003 | $0.00132 |
Grade A, and why
infrastructure scanned grade A with 0 findings 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 1mo 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Infrastructure Management
Framework for managing infrastructure as code, deployments, and disaster recovery.
Infrastructure as Code (IaC) Best Practices
Principles
- Version control everything — All infrastructure configs in Git
- Idempotent — Running same config multiple times produces same result
- Modular — Reusable modules for common patterns
- Documented — README for each module, inline comments for complex logic
- Tested — Validate configs before applying (terraform validate, linting)
Workflow
- Plan — Review changes, estimate impact
- Validate — Run validation/linting
- Review — Code review for infrastructure changes
- Apply — Deploy in stages (dev → staging → prod)
- Verify — Confirm changes work as expected
- Document — Update architecture docs
Change Management
- Small changes: Direct PR, single reviewer
- Medium changes: PR with 2 reviewers, staging test
- Large changes: RFC, architecture review, staged rollout
Deployment Strategies
Blue-Green Deployment
- Two identical environments: Blue (current), Green (new)
- Switch traffic from Blue to Green instantly
- Rollback: Switch back to Blue if issues
- Pros: Zero downtime, instant rollback
- Cons: Requires 2x capacity during deployment
Canary Deployment
- Gradual rollout: 5% → 25% → 50% → 100%
- Monitor metrics at each stage
- Rollback: Stop rollout if metrics degrade
- Pros: Risk mitigation, gradual validation
- Cons: Slower deployment, requires monitoring
Rolling Deployment
- Update instances one at a time
- Maintains capacity during rollout
- Rollback: Stop rollout, revert remaining instances
- Pros: No capacity overhead
- Cons: Partial version running, slower rollback
Feature Flags
- Toggle features without deployment
- Gradual rollout: Enable for % of users
- Instant rollback: Disable flag
- A/B testing: Compare feature variants
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.
- 1mo ago First seen · 191 lines · 33 tokens per session scan A ebf8e6b2a77e
infrastructure is a skill published in the GitHub repository saolalab/clawforce (38 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 33 tokens to every session and 1,318 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
linkerd-patterns
Implement Linkerd service mesh patterns for lightweight, security-focused service mesh deployments. Use when setting up Linkerd, configuring traffic policies, or implementing zero-trust networking with minimal overhead.
cost-optimization
Optimize cloud costs across AWS, Azure, GCP, and OCI through resource rightsizing, tagging strategies, reserved instances, and spending analysis. Use when reducing cloud expenses, analyzing infrastructure costs, or implementing cost governance policies.
istio-traffic-management
Configure Istio traffic management including routing, load balancing, circuit breakers, and canary deployments. Use when implementing service mesh traffic policies, progressive delivery, or resilience patterns.
tcapi
A helper for managing Tencent Cloud resources through Tencent Cloud's command-line API tool. Tencent Cloud is a cloud-services provider offering products such as virtual servers, storage, networks, and containers.
mcore-run-on-slurm
How to launch distributed Megatron-LM training jobs on a SLURM cluster. Covers a minimal sbatch skeleton, environment-variable setup for torch.distributed.run, CUDADEVICEMAXCONNECTIONS rules across hardware and parallelism modes, container conventions, monitoring, and per-rank failure diagnosis.
nemo-automodel-launcher-config
Configure NeMo AutoModel job launches for interactive runs, Slurm clusters, and SkyPilot cloud execution.