Review code using shared OpenClaw instructions and a Python helper, while also following the target repository’s review requirements. This skill points to a common installation that supplies the actual review procedure.
Structured code review through the shared OpenClaw agent-skills installation.
Review the instructions the agent will receive before you install.
Use the canonical autoreview skill.
Read the complete installed ~/.agents/skills/autoreview/SKILL.md and the references
it requires before reviewing. If installed at another operator-selected location,
use that installation. This repository entrypoint contains no review implementation.
If the skill is missing, reuse or clone https://github.com/openclaw/agent-skills
and run python3 scripts/install-skills autoreview from that checkout. On Windows,
use python; --mode copy is available when symlinks are unavailable.
Run the shared scripts/autoreview helper with Python from the repository being
reviewed, preserving its working directory. Follow this repository's review
requirements in addition to the canonical skill.
Keep shared fixes and instructions upstream in openclaw/agent-skills. Update
the shared checkout once for all symlinked consumers; reinstall copy-mode skills
after updating their source. Do not add repository-local helpers or test copies.
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Create and manage Axiom alert rules and notification destinations through its API. Connect alerts to email, Slack, or webhooks, check monitor history, and adjust thresholds and evaluation schedules to address excessive or missing alerts.
Investigate production incidents and bugs using logs, metrics, and code evidence. The skill guides hypothesis testing, root cause analysis, fix validation, and reusable investigation notes, with access to configured observability tools such as Axiom.
Design and build Axiom dashboards from logs or metrics, the numerical measurements of system behavior. Create charts, filters, and layouts for monitoring and reporting, or migrate existing Splunk and Grafana panels while validating queries against available data.
Drafts, previews, sends, and records emails for existing ClawHub content rights cases. It supports publisher removal notices and requester updates, requires approval of the final draft, and preserves the exact correspondence in the case record.
Apply ClawHub-specific rules when developing with Convex, including deployment targeting, runtime checks, data migrations, search performance, and skill statistics. It also directs specialized work to the appropriate companion skills.
Support ClawHub staff moderation through its local admin tool, including skill reports, removals and restores, user restrictions, publisher and package management, and staff email, with approval checks and verification after changes.