ha-diagnostics-augment

ha-diagnostics-augment is a skill for Claude Code from nolte/claude-home-assistant. It costs 199 tokens per session (2,039 once invoked), scanned A, original, MIT.

A skill for adding structured diagnostics to an existing Home Assistant custom integration. Diagnostics are technical information that helps explain an integration's state while hiding sensitive values.

In plain words
What is it for?
Use it to create or update diagnostics.py for a Home Assistant integration. It supports configuration-entry and, optionally, device diagnostics.
Why use it?
It extends the basic diagnostics scaffold and ensures returned information follows the project's rules, including agreed redaction of credentials and identifying data.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the claude-home-assistant plugin — 45 skills, 11 agents shipped together

Good fit Use it to create or update diagnostics.py for a Home Assistant integration. It supports configuration-entry and, optionally, device diagnostics.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/nolte/claude-home-assistant/ha-diagnostics-augment
Install

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.

Any agent
npx skills add nolte/claude-home-assistant --skill ha-diagnostics-augment
Clone the repo
git clone --depth 1 https://github.com/nolte/claude-home-assistant

Made for: Claude Code.

Or install claude-home-assistant, the plugin that ships this one along with the rest of its 45 skills, 11 agents.

Wrote 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.

agentmods badge for ha-diagnostics-augment

README.md
[![agentmods](https://agentmods.dev/badge/skills/nolte/claude-home-assistant/ha-diagnostics-augment/github.svg)](https://agentmods.dev/skills/nolte/claude-home-assistant/ha-diagnostics-augment)
Your own site
<a href="https://agentmods.dev/skills/nolte/claude-home-assistant/ha-diagnostics-augment"><img src="https://agentmods.dev/badge/skills/nolte/claude-home-assistant/ha-diagnostics-augment/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.

agentmods 80×15 button for ha-diagnostics-augment

Your own site · 80×15
<a href="https://agentmods.dev/skills/nolte/claude-home-assistant/ha-diagnostics-augment"><img src="https://agentmods.dev/badge/skills/nolte/claude-home-assistant/ha-diagnostics-augment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 199 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,039 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00199 $0.02039
Opus 5 $0.00100 $0.01019
Sonnet 5 $0.00040 $0.00408
Haiku 4.5 $0.00020 $0.00204

Measured 9d ago against content hash 76c3a7937b39, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

ha-diagnostics-augment 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 9d 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.

skills/ha-diagnostics-augment/SKILL.md · 108 lines

How it starts

The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.

HA Diagnostics Augment

Spec: spec/claude/ha-diagnostics-augment/en.md (EN canonical) / spec/claude/ha-diagnostics-augment/de.md (DE translation).

Why this is a skill, not an agent

  • Human-visible augmentation surface — the user describes the integration and reads back diagnostics.py, the TO_REDACT set, and the conformance report; a skill keeps this on the visible command surface, like the sibling augment skills (ha-config-flow-augment, ha-coordinator-add, ha-repairs-add, ha-device-automation-add).
  • Mid-flow interactivity — the redaction-key classification (which entry.data fields are credentials/identifiers/coordinates) is a per-run dialogue the user confirms before generation.
  • Bounded, inline generation — one module plus its TO_REDACT set and the dump structure fit inline; no isolated agent context is needed.
  • Counter-dimension considered: the derive→validate loop could be an agent, but the redaction-key classification belongs in the user's working context; skill wins.

When this skill activates

Use this skill to enrich an existing integration's diagnostics beyond the scaffold baseline — a complete, structured async_get_config_entry_diagnostics dump (and optionally async_get_device_diagnostics) that routes every sensitive field through async_redact_data and includes redacted coordinator snapshots.

When NOT to activate

  • auditing redaction gaps across modules (findings report) → ha-security-audit
  • the bare diagnostics stub at greenfield creation → ha-integration-scaffold
  • scoring the diagnostics quality-scale rule across all rules → ha-quality-scale-audit / ha/quality-scale
  • deploying/importing into a running HA instance → out of scope

Hard rules

  1. Existing integration only. custom_components/<domain>/manifest.json must exist. When diagnostics.py already exists, edit it — never blindly overwrite.
  2. Read spec/ha/diagnostics/en.md first. Do not generate from memory.
  3. async_get_config_entry_diagnostics contract. Export async_get_config_entry_diagnostics(hass, entry) -> dict as a top-level async function — HA invokes it automatically on "Download Diagnostics". Optionally export async_get_device_diagnostics(hass, entry, device) -> dict with the same redaction contract.
  4. async_redact_data is mandatory. Wrap every entry.data and entry.options lookup — and every coordinator nesting that carries sensitive fields — in homeassistant.components.diagnostics.async_redact_data(..., TO_REDACT). Never use manual logic (if "api_key" in d: d["api_key"] = "***"), a manual "REDACTED" string, or field deletion (del d["api_key"]); **REDACTED** preserves length/format debugging and is the HA convention.
  5. Module-constant TO_REDACT frozenset. Define TO_REDACT as a module constant (or in const.py when shared across hooks) holding every entry.data key classified as a credential or identifier — typically api_key, password, token, secret, auth, bearer, plus integration-specific tenant/account slugs. Keep it in sync with the entry.data schema.
  6. Identifiers and coordinates too. Include multi-tenant identifiers (tenant_slug, tenant_id, org_id) and coordinates (latitude, longitude) in TO_REDACT — identifying, therefore kept out of forum reports.
  7. Coordinator data in the dump. Include the current coordinator.data of every registered coordinator and redact it when the API response carries sensitive fields; reduce to a subset only when the full dump would be too large. Never dump logs or stack traces.
  8. Derive, don't guess. Derive the entry.data / entry.options key space from the config flow and setup; ask when uncertain.
  9. Name per spec/ha/naming-conventions/en.md and verify HA internals against the official docs (see spec/ha/upstream-docs-verification/en.md).

Read the full file on GitHub · 108 lines

Changes

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.

  1. 9d ago First seen · 108 lines · 199 tokens per session scan A 76c3a7937b39

Subscribe to this mod's changes

ha-diagnostics-augment is a skill published in the GitHub repository nolte/claude-home-assistant (1 stars, last pushed 1mo ago), licensed MIT. It adds 199 tokens to every session and 2,039 once invoked, about $0.0010 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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