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energy

Use when analyzing Home Assistant energy data — consumption, solar production, battery, grid costs, per-device usage — or safely editing Energy dashboard sources and tracked devices through HA NOVA Relay.

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Precio sin confirmar★ 21 Estrellas de GitHubRegistro actualizado · 14 sept 2026agent-skill

Resumen

Leer documentación completa

Documentación de origen, no instrucciones para este sitio. Revisa los permisos antes de ejecutar comandos.

HA NOVA Energy

Scope

Analysis (read-only):

energy config overview + misconfiguration triage (energy/validate)
consumption/production/cost reports over bounded periods
per-device ranking and cost (fixed or dynamic prices)
solar/battery/grid KPIs: self-sufficiency, self-consumption, battery round-trip
period comparisons (previous period, same period last year)

Config (gated writes):

add/update/remove energy sources and tracked devices via energy/save_prefs

Not in scope:

dashboard cards/views (ha-nova:dashboard)
generic entity history/logbook (ha-nova:history)
statistics repair (sum spikes, orphaned statistics): ha-nova:maintenance
creating sensors or integrations that produce new energy data (energy sensor from a power sensor → ha-nova:helper, type integration)

Bootstrap (once per session)

Read and follow ../ha-nova/session-bootstrap.md. Verify relay CLI: ha-nova relay health If this fails: ha-nova setup

Relay Contract

File-based requests: ha-nova relay ws --data-file <payload-file>; --out <result-file> for large responses. WS body: .data (skills/ha-nova/relay-api.md → Standard Envelope). Schemas, KPI formulas, and analysis recipes: skills/energy/energy-reference.md — read it before any config write or KPI computation.

Flow

Overview

WS {"type":"energy/get_prefs"} → sources + tracked devices. Error ERR_NOT_FOUND ("No prefs") means the dashboard was never configured — offer initial setup instead of failing. Report grouped: sources first (grid/solar/battery/gas/water), then devices (count + notable entries). Run WS {"type":"energy/validate"} in the same pass; its issue lists are parallel to config order — map every issue to its source/device and name the concrete fix (issue table in the reference).

Analysis

Resolve statistic IDs from prefs, then query recorder/statistics_during_period with types:["change"] and units:{"energy":"kWh"} over a bounded window (default: last 30 days). Follow the statistics contract in the reference exactly: HA-local day boundaries (weeks start Monday), ms-epoch timestamps, missing buckets count as 0, negative change is legal, 5minute period only reaches back ~10 days. Compute KPIs with the formulas in the reference so numbers match the HA UI; label documented approximations as such. Present cost figures as estimates — HA cost math never equals the utility bill (standing charges, VAT, official metering). Never: diff raw total_increasing states (use statistics change), report peak watts from energy-only statistics (only hourly averages exist — say so), present a partial day/month as a complete period (label it and compare like-for-like), or rebuild an EV manager's session history (evcc and similar expose their own statistics entities — read those).

Config edit (read → merge → save)

Fresh energy/get_prefs immediately before composing the save — never reuse an earlier read.
Detect the grid schema generation from the data (flow_from present = legacy nested; flat keys = HA 2026.3+). Emit the same generation; never mix. With no existing grid source to detect from, pick by HA version (GET /api/config → version; 2026.3+ = flat, else legacy). Preserve every field you do not edit verbatim, including unknown keys (power_config, stat_soc, name).
Mutate the returned list. save_prefs replaces the entire list for every key present — send only the top-level keys you touched, each as its complete list (canonical payload in the reference).
Preview the planned change: the exact entries added/changed/removed plus the count invariant (count before ± changes = count after). Say explicitly: removing a device stops tracking only — its recorded statistics stay.
Confirmation bound to this exact preview (context skill → Active Preview Confirmation): natural for a single add/change/remove; a save that empties or wholesale-replaces a list on a configured instance is destructive — typed confirmation code (context skill → Confirmation Tiers). Before any save that REMOVES entries (a single source/device removal included) or empties/wholesale-replaces a list, capture the auto config snapshot of the fresh pre-save get_prefs read (category energy, fixed name auto-prefs — the prefs are one document without item ids; skills/ha-nova/config-snapshots.md; on capture failure follow its capture-failure stop). Then run the drift check before applying (skills/ha-nova/write-safety.md → Drift check before apply): re-read get_prefs immediately before the save and compare it against the basis this preview was composed from. On first-time setup the basis is absence: a second ERR_NOT_FOUND means nothing changed and the save proceeds, while prefs that exist now expire the confirmation. On any other foreign change STOP — the confirmation expired, recompose and preview again. save_prefs replaces whole lists with no locking, so a source another client added in the meantime would vanish without a trace. Then WS energy/save_prefs (fails unless the App's configured HA token has admin rights).
Verify: re-read get_prefs (the save response echoes the new prefs — still re-read), confirm the invariant and that every untouched entry is deep-equal to the fresh pre-save read, then run energy/validate — a successful save does NOT prove the config works (dangling statistic IDs are accepted silently). Mention that other open dashboard tabs need a reload.

Initial setup after ERR_NOT_FOUND: treat every list as empty — compose only the keys being populated (count before = 0) and continue at step 4.

Write guards (schema details in the reference):

every grid source needs cost_adjustment_day (default 0); at most one of entity_energy_price/number_energy_price per direction
never set price fields on an external statistic (: in the ID) unless stat_cost is already set — HA 2026.4+ rejects the save
never invent stat_cost — leave it null with a price field set and HA creates the cost sensor itself; resolve actual cost statistics via energy/info → cost_sensors
included_in_stat must reference a stat_consumption present in the same list, without cycles — HA does not validate this
referenced statistics must exist (recorder/list_statistic_ids), should belong to a live entity (validate reports entity_not_defined otherwise), and must meet the sensor prerequisites in the issue table

Error Handling

ERR_NOT_FOUND on get_prefs: unconfigured dashboard, not a failure.
Save rejected: report HA's message verbatim; re-read prefs before any retry — another client may have written meanwhile.
Full relay error taxonomy: skills/ha-nova/relay-api.md → Error Handling.

Output Format

Apply skills/ha-nova/output-rules.md. Write previews, delete confirmations, and results render as the Cards defined there.

Energy / Status
Planned change
Options
Verification
Next step

Use stable localized slot labels in this order; omit empty slots. Analysis answers render the Report shape; rankings render the List Frame (output-rules.md) — never raw JSON.

Safety

Preview before write: nothing is saved until the user confirms the shown preview.
Confirmation binds to the displayed preview and expires on any change to target, payload, endpoint, or scope (context skill → Active Preview Confirmation).
Pre-preview phrases ("do it", "go ahead", "implement the plan") authorize drafting and preview only — never the write itself.
Delete and destructive operations require the typed confirmation code confirm:<token> verbatim; "yes" or any natural-language reply is invalid.
Never guess entity, service, or config IDs — resolve them or ask.
Home Assistant is reached exclusively through ha-nova relay.
For any HA write this skill does not cover, STOP and invoke ha-nova:fallback first — never probe unfamiliar write endpoints.
Drafts follow skills/ha-nova/smallest-solution.md: the complete requested outcome in the simplest safe design, nothing for hypothetical future needs.
Config writes: preview + confirmation per save (natural for single edits; typed confirmation code for empty/wholesale-replace saves — step 5); verify by read-back + validate.
No update-revert — recovery after an entry-removing save is the auto-prefs config snapshot (restore = corrective save_prefs of the loaded document, skills/ha-nova/config-snapshots.md); otherwise a corrective save or HA Backups (see skills/ha-nova/write-safety.md).
Analysis flows are strictly read-only; never call save_prefs while answering an analysis question.

Ver fuente ↗

Metadatos del archivo

name: energy
description: Use when analyzing Home Assistant energy data — consumption, solar production, battery, grid costs, per-device usage — or safely editing Energy dashboard sources and tracked devices through HA NOVA Relay.
license: MIT
compatibility: Requires the ha-nova CLI (run 'ha-nova setup' first) and the HA NOVA Relay in Home Assistant (App, or standalone container on Container/Core).

Ver texto original

---
name: energy
description: Use when analyzing Home Assistant energy data — consumption, solar production, battery, grid costs, per-device usage — or safely editing Energy dashboard sources and tracked devices through HA NOVA Relay.
license: MIT
compatibility: Requires the ha-nova CLI (run 'ha-nova setup' first) and the HA NOVA Relay in Home Assistant (App, or standalone container on Container/Core).
---

# HA NOVA Energy

## Scope

Analysis (read-only):
- energy config overview + misconfiguration triage (`energy/validate`)
- consumption/production/cost reports over bounded periods
- per-device ranking and cost (fixed or dynamic prices)
- solar/battery/grid KPIs: self-sufficiency, self-consumption, battery round-trip
- period comparisons (previous period, same period last year)

Config (gated writes):
- add/update/remove energy sources and tracked devices via `energy/save_prefs`

Not in scope:
- dashboard cards/views (`ha-nova:dashboard`)
- generic entity history/logbook (`ha-nova:history`)
- statistics repair (sum spikes, orphaned statistics): `ha-nova:maintenance`
- creating sensors or integrations that produce new energy data (energy sensor from a power sensor → `ha-nova:helper`, type `integration`)

## Bootstrap (once per session)

Read and follow `../ha-nova/session-bootstrap.md`.
Verify relay CLI: `ha-nova relay health`
If this fails: `ha-nova setup`

## Relay Contract

File-based requests: `ha-nova relay ws --data-file <payload-file>`; `--out <result-file>` for large responses. WS body: `.data` (`skills/ha-nova/relay-api.md` → Standard Envelope).
Schemas, KPI formulas, and analysis recipes: `skills/energy/energy-reference.md` — read it before any config write or KPI computation.

## Flow

### Overview
WS `{"type":"energy/get_prefs"}` → sources + tracked devices. Error `ERR_NOT_FOUND` ("No prefs") means the dashboard was never configured — offer initial setup instead of failing. Report grouped: sources first (grid/solar/battery/gas/water), then devices (count + notable entries). Run WS `{"type":"energy/validate"}` in the same pass; its issue lists are parallel to config order — map every issue to its source/device and name the concrete fix (issue table in the reference).

### Analysis
Resolve statistic IDs from prefs, then query `recorder/statistics_during_period` with `types:["change"]` and `units:{"energy":"kWh"}` over a bounded window (default: last 30 days). Follow the statistics contract in the reference exactly: HA-local day boundaries (weeks start Monday), ms-epoch timestamps, missing buckets count as 0, negative change is legal, `5minute` period only reaches back ~10 days.
Compute KPIs with the formulas in the reference so numbers match the HA UI; label documented approximations as such. Present cost figures as estimates — HA cost math never equals the utility bill (standing charges, VAT, official metering).
Never: diff raw `total_increasing` states (use statistics `change`), report peak watts from energy-only statistics (only hourly averages exist — say so), present a partial day/month as a complete period (label it and compare like-for-like), or rebuild an EV manager's session history (evcc and similar expose their own statistics entities — read those).

### Config edit (read → merge → save)
1. Fresh `energy/get_prefs` immediately before composing the save — never reuse an earlier read.
2. Detect the grid schema generation from the data (`flow_from` present = legacy nested; flat keys = HA 2026.3+). Emit the same generation; never mix. With no existing grid source to detect from, pick by HA version (`GET /api/config` → `version`; 2026.3+ = flat, else legacy). Preserve every field you do not edit verbatim, including unknown keys (`power_config`, `stat_soc`, `name`).
3. Mutate the returned list. `save_prefs` replaces the entire list for every key present — send only the top-level keys you touched, each as its complete list (canonical payload in the reference).
4. Preview the planned change: the exact entries added/changed/removed plus the count invariant (count before ± changes = count after). Say explicitly: removing a device stops tracking only — its recorded statistics stay.
5. Confirmation bound to this exact preview (context skill → Active Preview Confirmation): natural for a single add/change/remove; a save that empties or wholesale-replaces a list on a configured instance is destructive — typed confirmation code (context skill → Confirmation Tiers). Before any save that REMOVES entries (a single source/device removal included) or empties/wholesale-replaces a list, capture the auto config snapshot of the fresh pre-save `get_prefs` read (category `energy`, fixed name `auto-prefs` — the prefs are one document without item ids; `skills/ha-nova/config-snapshots.md`; on capture failure follow its capture-failure stop). Then run the drift check before applying (`skills/ha-nova/write-safety.md` → Drift check before apply): re-read `get_prefs` immediately before the save and compare it against the basis this preview was composed from. On first-time setup the basis is absence: a second `ERR_NOT_FOUND` means nothing changed and the save proceeds, while prefs that exist now expire the confirmation. On any other foreign change STOP — the confirmation expired, recompose and preview again. `save_prefs` replaces whole lists with no locking, so a source another client added in the meantime would vanish without a trace. Then WS `energy/save_prefs` (fails unless the App's configured HA token has admin rights).
6. Verify: re-read `get_prefs` (the save response echoes the new prefs — still re-read), confirm the invariant and that every untouched entry is deep-equal to the fresh pre-save read, then run `energy/validate` — a successful save does NOT prove the config works (dangling statistic IDs are accepted silently). Mention that other open dashboard tabs need a reload.

Initial setup after `ERR_NOT_FOUND`: treat every list as empty — compose only the keys being populated (count before = 0) and continue at step 4.

Write guards (schema details in the reference):
- every grid source needs `cost_adjustment_day` (default `0`); at most one of `entity_energy_price`/`number_energy_price` per direction
- never set price fields on an external statistic (`:` in the ID) unless `stat_cost` is already set — HA 2026.4+ rejects the save
- never invent `stat_cost` — leave it `null` with a price field set and HA creates the cost sensor itself; resolve actual cost statistics via `energy/info` → `cost_sensors`
- `included_in_stat` must reference a `stat_consumption` present in the same list, without cycles — HA does not validate this
- referenced statistics must exist (`recorder/list_statistic_ids`), should belong to a live entity (validate reports `entity_not_defined` otherwise), and must meet the sensor prerequisites in the issue table

## Error Handling

- `ERR_NOT_FOUND` on `get_prefs`: unconfigured dashboard, not a failure.
- Save rejected: report HA's message verbatim; re-read prefs before any retry — another client may have written meanwhile.
- Full relay error taxonomy: `skills/ha-nova/relay-api.md` → Error Handling.

## Output Format

Apply `skills/ha-nova/output-rules.md`. Write previews, delete confirmations, and results render as the Cards defined there.

- `Energy` / `Status`
- `Planned change`
- `Options`
- `Verification`
- `Next step`

Use stable localized slot labels in this order; omit empty slots. Analysis answers render the Report shape; rankings render the List Frame (output-rules.md) — never raw JSON.

## Safety

- Preview before write: nothing is saved until the user confirms the shown preview.
- Confirmation binds to the displayed preview and expires on any change to target, payload, endpoint, or scope (context skill → Active Preview Confirmation).
- Pre-preview phrases ("do it", "go ahead", "implement the plan") authorize drafting and preview only — never the write itself.
- Delete and destructive operations require the typed confirmation code `confirm:<token>` verbatim; "yes" or any natural-language reply is invalid.
- Never guess entity, service, or config IDs — resolve them or ask.
- Home Assistant is reached exclusively through `ha-nova relay`.
- For any HA write this skill does not cover, STOP and invoke `ha-nova:fallback` first — never probe unfamiliar write endpoints.

- Drafts follow `skills/ha-nova/smallest-solution.md`: the complete requested outcome in the simplest safe design, nothing for hypothetical future needs.

- Config writes: preview + confirmation per save (natural for single edits; typed confirmation code for empty/wholesale-replace saves — step 5); verify by read-back + validate.
- No update-revert — recovery after an entry-removing save is the `auto-prefs` config snapshot (restore = corrective `save_prefs` of the loaded document, `skills/ha-nova/config-snapshots.md`); otherwise a corrective save or HA Backups (see `skills/ha-nova/write-safety.md`).
- Analysis flows are strictly read-only; never call `save_prefs` while answering an analysis question.

Revisar el código fuente

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Licencia: MIT
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Revisar antes de instalar: Evitar instalación automática

Licencia: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
Financial research output is not financial advice; require human review before any live investment decision
Low GitHub adoption signal
Falta aprobación de revisión por IA
Financial research output is not financial advice; require human review before any live investment decision.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 21 GitHub stars
Stars/forks activity: 21 stars, 1 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

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Repositorio fuente: markusleben/ha-nova
Licencia: MIT
Versión: Unknown
Último push de GitHub: 13 sept 2026
Registro actualizado: 14 sept 2026
Ruta de instrucciones: skills/energy/SKILL.md @ 8e63c4ed2bd0

Versión declarada en el registro; consulta las versiones de la fuente.

Calidad

55/100

Prometedor

Confianza

57/100

Do not auto-install

Auditoría

70/100

Requiere revisión

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Dependency or permission surface needs review
Permission surface may require sandboxing
Financial research output is not financial advice; require human review before any live investment decision
Low GitHub adoption signal
Falta aprobación de revisión por IA
Financial research output is not financial advice; require human review before any live investment decision.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 21 GitHub stars
Stars/forks activity: 21 stars, 1 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

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      "agentOutcomes": "No agent outcome data yet"
    },
    "outcome_evidence": {
      "total": 0,
      "successes": 0,
      "failures": 0,
      "not_relevant": 0,
      "success_rate": null,
      "recent_success_rate": null,
      "recent_failure_rate": null,
      "install_attempts": 0,
      "install_success_rate": null,
      "risk_blocked": 0,
      "setup_required": 0,
      "avg_output_quality": null,
      "production_outcomes": 0,
      "last_outcome_at": null,
      "label": "No agent outcome data yet"
    },
    "auto_install": {
      "allowed": false,
      "sandbox_required": true,
      "reason": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
    },
    "best_for": [
      "research",
      "agent-skill"
    ],
    "known_risks": [
      "AI review approval is missing",
      "Financial research output is not financial advice; require human review before any live investment decision.",
      "Low GitHub adoption signal",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "GitHub adoption: 21 GitHub stars",
      "Stars/forks activity: 21 stars, 1 forks; issue activity unavailable in current metadata",
      "Dependency/runtime risk: command execution surface, credential or environment access"
    ]
  },
  "agent_proven": {
    "version": "agent-proven-v1",
    "score": 0,
    "tier": "unproven",
    "label": "Needs first agent run",
    "summary": "No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.",
    "metrics": {
      "totalOutcomes": 0,
      "successfulOutcomes": 0,
      "failedOutcomes": 0,
      "installAttempts": 0,
      "installSuccessRate": null,
      "successRate": null,
      "recentSuccessRate": null,
      "recentFailureRate": null,
      "riskBlocked": 0,
      "setupRequired": 0,
      "notRelevant": 0,
      "avgOutputQuality": null,
      "avgTimeToUsefulMs": null,
      "productionOutcomes": 0,
      "humanReviewRequired": 0,
      "uniqueAgents": 0,
      "lastOutcomeAt": null
    },
    "signals": [],
    "penalties": [
      "No real agent outcome evidence yet"
    ]
  },
  "audit": {
    "score": 70,
    "risk_level": "needs_review",
    "risk_label": "Needs review",
    "warnings": [
      "Dependency or permission surface needs review",
      "Permission surface may require sandboxing",
      "Financial research output is not financial advice; require human review before any live investment decision",
      "Low GitHub adoption signal",
      "AI review approval is missing",
      "Financial research output is not financial advice; require human review before any live investment decision.",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution"
    ]
  },
  "safety_gate": {
    "tier": "blocked",
    "label": "Blocked for auto-install",
    "auto_install_policy": "block",
    "auto_install_allowed": false,
    "human_review_required": true,
    "blocked": true,
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
  },
  "quality": {
    "score": 55,
    "label": "Promising"
  },
  "supply": {
    "track": "Research and knowledge work",
    "scenario": "Research agents",
    "maintenance": "29d since push",
    "risk": "Needs review"
  },
  "alternative_skills": [],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "production agents without a repository review",
    "Low GitHub adoption signal",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "Financial research output is not financial advice; require human review before any live investment decision",
    "AI review approval is missing"
  ],
  "agent_contract": {
    "task_input": "Use energy in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 65/100 Manual review",
      "Audit: 70/100 Needs review",
      "Safety: 26/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "markusleben-energy (energy)",
      "install_command": "npx skills add markusleben/ha-nova --skill energy",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "markusleben-energy",
      "task": "Use energy in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/markusleben-energy",
    "api": "https://www.openagentskill.com/api/agent/skills/markusleben-energy",
    "audit": "https://www.openagentskill.com/skills/markusleben-energy/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=markusleben-energy&task=Use%20energy%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20energy%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20energy%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/markusleben-energy/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/markusleben-energy"
  }
}

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Creador: markusleben
Fuente: markusleben/ha-nova
Indexado por: Índice comunitario de OpenAgentSkill

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