Action Suggester

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...

Security Scan

This instruction-only skill is internally consistent with its stated purpose: it generates non-binding follow-up suggestions, requests no credentials or installs, and includes explicit (textual) boundaries against performing actions.

Purpose & Capability

The name/description (

Assessment

Before installing: 1) Confirm your agent/runtime will enforce 'do not execute' semantics (the SKILL.md statements are instructions, not technical enforcement). 2) Provide only the minimum PII (phone numbers, names) required for suggestions and ensure downstream systems won't leak those fields. 3) Require human/Supervisor confirmation before any execution and test the skill with dummy data to validate schema handling. 4) Audit your agent chains to ensure no other skill or automation will act on the generated suggestions without explicit approval.

Produce ranked follow-up suggestions without taking any external action.

Quick Triggers

• 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.

Recommended Chain

summary-generator -> action-suggester -> supervisor confirmation

Execute Workflow

1. Accept input from Supervisor.
2. Validate input with references/action-input.schema.json.
3. Apply deterministic prioritization rules to propose follow-up items.
4. Emit actions with:
   • action_type in call, email, or visit
   • lead_id
   • description
5. Validate output with references/action-output.schema.json.
6. Return suggestions for human or Supervisor review only.

Enforce Boundaries

• 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.

Handle Errors

1. Return an empty action list when evidence is insufficient.
2. Reject inputs that fail schema validation.
3. Surface deterministic rule conflicts in plain text diagnostics.