From gaia-ops
Reference material for dispatch parameter extraction and prompt templates. The orchestrator's dispatch execution section covers the core principles -- load this skill for detailed templates and examples.
npx claudepluginhub metraton/gaia --plugin gaia-opsThis skill uses the workspace's default tool permissions.
On-demand reference for parameter extraction, prompt templates, and task
Triggers research for existing libraries, tools, and patterns before coding new features. Searches npm, PyPI, MCP/skills, GitHub; evaluates matches and decides adopt/extend/build.
Audits cross-stack repos (C++/Android/iOS/Web), classifies files as project/third-party/artifacts, detects embedded libraries, assigns module verdicts, generates interactive HTML reports.
Reorganizes X and LinkedIn networks: review-first pruning of low-value follows, priority-based add/follow recommendations, and drafts warm outreach in user's voice.
Share bugs, ideas, or general feedback.
On-demand reference for parameter extraction, prompt templates, and task classification details. The orchestrator's "Dispatch execution" identity section covers when and how to dispatch. Load this skill when you need the exact templates or extraction patterns.
| Measurable? | Improvable? | Type | Action |
|---|---|---|---|
| Yes | Yes (iterative) | agentic-loop | Build loop prompt with all params |
| Yes | No (pass/fail) | simple-task | Build focused prompt, no loop |
| Creatable | Yes | two-phase | Phase 1: create eval. Phase 2: agentic-loop |
| No | N/A | manual-review | Warn user, offer alternatives |
Required: goal, eval_command, metric, direction, threshold
Optional: max_iterations (default 20), files_in_scope, branch prefix
If any required param is missing -- ASK the user. Do not guess eval commands
or thresholds. See reference.md for extraction examples and confirmation
patterns.
For agentic-loop tasks, use the template in reference.md. The prompt MUST
include the Carga la skill agentic-loop header -- this triggers skill
injection in the agent.
For simple tasks, build a focused objective prompt without the loop header. For two-phase tasks, dispatch Phase 1 first (create eval), then Phase 2 (loop).
When the user wants recurring execution ("cada noche", "cron", "schedule"):
CronCreate with the built promptrecurring=falserecurring=true -- warn about 7-day limitreference.md for cron expression examplesWhen an agent returns loop_status in its json:contract:
"iterating" -- agent still working, wait"threshold_reached" / "complete" -- present: baseline -> final in N iterations"stopped" -- present what was achieved + why it stopped"blocked" -- present blocker, ask usereval_command -- the agent cannot measure progressagentic-loop skill handles that