Results for “discoverability”

Discovers and evaluates community skills from skills.sh and awesome-openclaw-skills when local skills don't cover a need, scoring credibility and installing top recommendations with permission.

Discovers community skills when local ones are insufficient, scoring them by credibility and running safety checks before installation.

Surface and clarify unknowns before prompting, log deviations during implementation, and verify understanding after, using HTML artifacts that pair prompts with outputs.

Use when users do not know which skill fits a task, need to search available skill catalogs, compare candidates, install a matching skill, or route work to the best existing capability.

Orchestrate token-heavy research, coding, and testing by delegating bounded tasks to cheaper subagents while reserving Claude Fable for architecture, synthesis, and final review.

Build and maintain a custom project skill repertoire. Always use at new project bootstrap and when users ask for new domain capabilities. Detect active assistant folders first, recommend at least 5 skills per search batch, confirm installs, normalize install paths, and regenerate workflow files.

Discover, compare, audit, repair, adapt, craft, run, debrief, and publish repeatable AI-agent loops for engineering workflows.