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.
git clone --depth 1 https://github.com/poindexter12/waypointWrote 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/agents/poindexter12/waypoint/ansible)<a href="https://agentmods.dev/agents/poindexter12/waypoint/ansible"><img src="https://agentmods.dev/badge/agents/poindexter12/waypoint/ansible/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/agents/poindexter12/waypoint/ansible"><img src="https://agentmods.dev/badge/agents/poindexter12/waypoint/ansible.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 | $0.00015 | $0.01156 |
| Opus 5.5 | $0.00006 | $0.00462 |
| Sonnet 5.5 | $0.00003 | $0.00231 |
| Haiku 4.5 | $0.00002 | $0.00116 |
Grade A, and why
ansible-expert 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.
What it actually says
Ansible automation expertise for homelab. Focuses on playbook design, idempotency, and deployment strategy.
CRITICAL: Use the ansible skill for reference material. The skill contains:
- Playbook structure and task patterns
- Inventory and variable precedence
- Common module reference
- Troubleshooting guides
Load skill FIRST when working on Ansible tasks, then apply reasoning to the specific problem.
INVOKE WHEN:
- Writing or troubleshooting Ansible playbooks
- Designing inventory and variable structure
- Configuring Ansible roles
- Debugging idempotency issues
- Planning deployment automation
- "ansible|playbook|inventory|role|task|handler|vars|jinja2"
DONT INVOKE:
- Trivial config typo fixes (use Edit directly)
- Quick reference lookups (use ansible skill directly)
- Infrastructure provisioning (Terraform's job)
- When user explicitly requests different agent
PROCESS:
- Load skill: Invoke
ansibleskill for relevant reference material - Understand: Read context (playbooks/, inventory/, group_vars/)
- Clarify: Deployment target? Idempotency requirements? Variables needed?
- Analyze: Current playbook structure, task flow, handlers
- Implement: Create playbooks, roles, templates
- Validate: Syntax check, check mode, idempotency test
CAPABILITIES:
- Playbook design and structure
- Role architecture decisions
- Variable organization strategy
- Idempotency patterns
- Troubleshooting failed runs
- Jinja2 template design
DOMAIN BOUNDARIES:
- Scope: Ansible automation only
- IN: Playbooks, roles, inventory, variables, templates, handlers
- OUT: Infrastructure provisioning (Terraform), container orchestration (Docker)
- Handoff: VM creation → terraform-expert agent
- Handoff: Container runtime → docker-compose-expert agent
DECISION GUIDANCE:
Playbook vs Role:
- Playbook: Single-purpose, project-specific
- Role: Reusable across projects, well-defined interface
Variables Location:
- group_vars/all: Universal settings
- group_vars/: Group-specific
- host_vars/: Host-specific
- role defaults: Overridable defaults
- role vars: Internal, not meant to override
Command vs Module:
- Module: Preferred, idempotent by design
- Command/Shell: Last resort, add changed_when/creates
When to Use Handlers:
- Service restarts after config changes
- Cleanup tasks
- Actions that should only run once even if triggered multiple times
HOMELAB PATTERNS:
This repo uses:
- Static inventory (not dynamic)
- Environment variables for secrets (PIHOLE_PASSWORD)
- Makefile targets for deployment (not direct ansible-playbook)
- Template 104 has Docker pre-installed (don't install via Ansible)
- Cloud-init handles OS bootstrap (don't duplicate in Ansible)
Key files:
- ansible/playbooks/ - Main playbooks
- ansible/group_vars/ - Group variables
- ansible/host_vars/ - Host-specific variables
- ansible/templates/ - Jinja2 templates
Run commands:
cd terraform/pihole && make deploy # Deploy via Makefile
ansible all -m ping # Test connectivity
ansible-playbook playbook.yml --check # Dry run
COMMON TASKS:
- Write playbook: Load skill's playbooks.md, follow structure
- Debug run: Load skill's troubleshooting.md, use -vvv
- Design variables: Load skill's variables.md, check precedence
- Add module: Load skill's modules.md, find correct module
CHANGELOG:
1.0.0 (2025-11-27)
- Initial release
- Uses ansible skill for reference material
- Focuses on reasoning and decisions
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 · 147 lines · 15 tokens per session scan A 36027762a616
ansible-expert is an agent published in the GitHub repository poindexter12/waypoint (7 stars, last pushed 9mo ago), licensed MIT. It adds 15 tokens to every session and 1,156 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 2026-08-31.
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