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 agentmods add skills/home-assistant/core/ha-reviewnpx skills add home-assistant/core --skill ha-reviewgit clone --depth 1 https://github.com/home-assistant/coreWhat 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 | $0.00050 | $0.00472 |
| Opus 5 | $0.00025 | $0.00236 |
| Sonnet 5 | $0.00010 | $0.00094 |
| Haiku 4.5 | $0.00005 | $0.00047 |
Grade A, and why
ha-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Review Code Changes
Scope:
- Unless instructed otherwise, review the full changes (the ones from the branch plus uncommitted ones) against the target branch. Resolve the base to an available ref (prefer
upstream/<base>, thenorigin/<base>, then local<base>) and reviewgit diff "$(git merge-base "$BASE_REF" HEAD)"; usedevas the default base.
Analyze the code changes for:
- Code quality and style consistency
- Potential bugs or issues
- Performance implications
- Security concerns
- Test coverage
- Documentation updates if needed
Quality scale:
- If the changes include a
quality_scale.yamlfile, run a subagent to verify all the added or modified rules, following theha-quality-scale-verifyskill. - Include the verification results in the final review comments.
Verification:
- After the review, run parallel subagents for each finding to double-check it.
- Spawn up to a maximum of 10 parallel subagents at a time.
- Gather the results from the subagents and summarize them in the final review comments.
IMPORTANT:
- Just review. DO NOT make any changes.
- Be constructive and specific in your comments.
- Suggest improvements where appropriate.
- No need to run tests or linters, just review the code changes.
- No need to highlight things that are already good.
Output format:
- List specific comments for each file/line that needs attention.
- In the end, summarize with an overall assessment (approve, request changes, or comment) and bullet point list of changes suggested, if any.
- Example output:
Overall assessment: request changes. - [CRITICAL] sensor.py:143 - Memory leak - [PROBLEM] data_processing.py:87 - Inefficient algorithm - [SUGGESTION] test_init.py:45 - Improve x variable name - Make sure to include the file and line number when possible in the bullet points.
- Example output:
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.
- today First seen · 46 lines · 50 tokens per session scan A 17041f35c9c5
ha-review is a skill published in the GitHub repository home-assistant/core (90,198 stars, last pushed today), licensed Apache-2.0. It adds 50 tokens to every session and 472 once invoked, about $0.0003 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.
Other skills, from other repositories
iot-developer
Expert in IoT development, microcontrollers, sensors, and MQTT protocols.
edge-iot
Edge computing, IoT protocols, and embedded systems integration.
acme-cse
Answer questions about the ACME oneM2M CSE open source project — installation, configuration, runtime options, protocol bindings, plugins, scripting, and development. Use this skill whenever the user asks anything about ACME CSE, oneM2M, acmecse, acme.ini, CSE setup, or running/configuring the ACME middleware, even if…
aether-iot-query
Use this skill when the user asks about a live AetherEdge runtime: channels, points, real-time values, history, alarms, rules, models, instances, routing, SHM health, service health, or system status. Use aether CLI commands to answer — do NOT inspect source code, local database files, or config YAMLs to answer…
aether-iot
Build, integrate, diagnose, or generate applications for the AetherEdge AI-native edge kernel. Use for AetherEdge onboarding, SDK compositions, device and topology clients, read-only operations UIs, MCP integration, Domain Packs, or governed IoT commands where live-state authority and physical-device safety must be…
devices-mcp-home
Live inventory of the user's smart home on this devices-mcp installation — cameras, Hue lights, Tapo P115 plugs, Netatmo weather, Ring, Nest Protect, Shelly sensors, and robots. Use when the user asks what devices they have, what's online, or wants a status summary before controlling hardware.