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 FernanMoreno/DomoAI --skill optimize-home-energygit clone --depth 1 https://github.com/FernanMoreno/DomoAIWrote 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/fernanmoreno/domoai/optimize-home-energy)<a href="https://agentmods.dev/skills/fernanmoreno/domoai/optimize-home-energy"><img src="https://agentmods.dev/badge/skills/fernanmoreno/domoai/optimize-home-energy/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/fernanmoreno/domoai/optimize-home-energy"><img src="https://agentmods.dev/badge/skills/fernanmoreno/domoai/optimize-home-energy.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 | $0.00020 | $0.01274 |
| Opus 5 | $0.00010 | $0.00637 |
| Sonnet 5 | $0.00004 | $0.00255 |
| Haiku 4.5 | $0.00002 | $0.00127 |
Grade A, and why
optimize-home-energy 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 3d 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Optimize home energy
This portable procedure coordinates context gathering, optimization and the existing plan boundary. It is usable by compatible Agent Skills hosts, but it does not grant authorization and it never calls a physical adapter directly.
Contract metadata
- Contract version:
v4 - Fixture reference:
tests/integration/test_core_skill.py - Safety owner: DomoAI runtime policy and plan executor
- Host mapping: every DomoAI operation uses one general
mcpconnection; hosts must not replace it with separate server instances, vendor calls or arbitrary solver code.
Declared operations
discover_devicesget_stateget_energy_contextoptimize_scenariovalidate_planexplain_solutionoperator_approvalcommit_or_schedule_bundle
Operation bindings
discover_devices→mcp.discover_devices(read)get_state→mcp.get_state(read)get_energy_context→mcp.get_energy_context(read)optimize_scenario→mcp.optimize_scenario(proposal)validate_plan→mcp.validate_plan(validation)explain_solution→mcp.explain_solution(read)operator_approval→operator.request_approval(approval)commit_or_schedule_bundle→mcp.commit_or_schedule_bundle(mutation)
Procedure
discover_devices— read the canonical inventory and identify controllable energy devices, their areas and capabilities.get_state— read current state, freshness and availability for the selected devices. Stop if required state is stale or unavailable and the operator has not accepted it as an assumption.get_energy_context— read the complete typed tariff, solar and optional battery context for the requested horizon. Stop if the provider cannot return a complete context or its runtime revision is stale.optimize_scenario— build a solver-neutral scenario with explicit horizon, resolution, units, loads, constraints and objectives. Request a proposal only.validate_plan— legacy persistent alias forprepare_plan; send the returned proposal through the runtime validation and policy boundary. Usepreview_planwhen the host needs an ephemeral read-only check. Never treat an optimizer result as authorization.explain_solution— explain selected slots, hard constraints, diagnostics and assumptions in user-facing language.operator_approval— if policy or risk requires confirmation, pause and ask the operator. For a bundle, approve the complete orderedbundle_digestshown in the explanation; the skill cannot approve its own plan.commit_or_schedule_bundle— hand the complete ordered bundle to the runtime-owned commit boundary with the bundle digest and per-member approval ids. The runtime performs preflight, durable scheduling or sequential physical execution, final revision/policy checks and recovery bookkeeping. It never infers rollback for an already written member.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago Changed · +9 lines c1c2d7db4898
- 10d ago First seen · 105 lines · 20 tokens per session scan A b6fd0e2e0785
optimize-home-energy is a skill published in the GitHub repository FernanMoreno/DomoAI (0 stars, last pushed 4d ago), licensed MPL-2.0. It adds 20 tokens to every session and 1,274 once invoked, about $0.0001 per session on Opus 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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