Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Generate non-binding follow-up action suggestions from lead summaries or lead lists. Use when users ask for next best actions, call list for hot leads, or fo...
Generate non-binding follow-up action suggestions from lead summaries or lead lists. Use when users ask for next best actions, call list for hot leads, or fo...
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Produce ranked follow-up suggestions without taking any external action.
Suggest next actions for today's P1 leads. Build a call/email/visit plan from summary. Draft follow-up queue for unresolved high-priority leads.
summary-generator -> action-suggester -> supervisor confirmation
Accept input from Supervisor. Validate input with references/action-input.schema.json. Apply deterministic prioritization rules to propose follow-up items. Emit actions with: action_type in call, email, or visit lead_id description Validate output with references/action-output.schema.json. Return suggestions for human or Supervisor review only.
Never execute suggested actions. Never send messages, emails, or calendar invites. Never write to database or stateful systems. Never parse raw chat exports. Never approve its own output for execution.
Return an empty action list when evidence is insufficient. Reject inputs that fail schema validation. Surface deterministic rule conflicts in plain text diagnostics.
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Largest current source with strong distribution and engagement signals.