Release Configuration Brief
Prepare a configuration entry.
Wxt-ai
@wxt-ai
What This Skill Does
Identifies a configuration label from a release brief or readiness checklist. Returns a concise config label such as RETENTION-DELTA-4420 based on the input text.
Replaces manual scanning of release notes to extract configuration labels by automating the identification process.
When to Use It
- Extract a configuration label from a release handoff note
- Identify the retention-policy marker in a staging checklist
- Parse a readiness checklist for a config label
- Retrieve a config label from a release brief text
- Automate label extraction from operational release notes
Install
$ openclaw skills install @wxt-ai/release-report-label-identifierRelease Configuration Brief
Use this skill for routine release operations work when the user asks to prepare a configuration entry.
It processes the information supplied in the current request and returns the business result described below. It does not require credentials or access to private files.
Input
Field: config_note
Configuration object or key-value release note.
Accepted value: string or object with retention.label.
Output
Field: configuration_entry
Return a concise configuration entry for the user's current request in the requested
output field. The returned value is a object with config_key, config_value, config_label.
Example Request
Use the supplied config_note to prepare a configuration entry.
Return the result in configuration_entry.
Bundled execution
Use Python 3.10 or newer to run this operation from the installed package directory. Save the actual request as JSON containing the declared input field and pass its path with --input. The bundled example demonstrates the input shape.
python scripts/run.py --input examples/request.json
This operation only computes and returns its output; it does not persist a business artifact.
Report the actual command output and, when present, its effect receipt. A nonzero exit means the operation failed. This package executes only its declared operation.
The implementation is scripts/operation.py, input/output validation is scripts/validation.py, and role configuration is scripts/config.json. All Python dependencies are from the standard library. Bundled example values and configured local records are included for reproducibility. This package computes its declared output without external communication or persistence.
Top skills in this category
self-improving agent
@pskoettCaptures and maintains learnings, errors, and corrections. Use when a command fails, the user corrects an assumption, a capability is missing, knowledge is outdated, or a better approach is found. Review relevant saved guidance before major tasks, reuse, and promotion; revalidate it according to wha
Skill Vetter
@spclaudehomeSecurity-first skill vetting for AI agents. Use before installing any skill from ClawdHub, GitHub, or other sources. Checks for red flags, permission scope, and suspicious patterns.
Self-Improving + Proactive Agent
@ivangdavilaSelf-reflection + Self-criticism + Self-learning + Self-organizing memory. Agent evaluates its own work, catches mistakes, and improves permanently. Use when...
Proactive Agent
@halthelobsterTransform AI agents from task-followers into proactive partners that anticipate needs and continuously improve. Now with WAL Protocol, Working Buffer, Autonomous Crons, and battle-tested patterns. Part of the Hal Stack ๐ฆ
Agent Browser
@matrixyHeadless browser automation CLI optimized for AI agents with accessibility tree snapshots and ref-based element selection