Works with the AI tools you already use
Local Agentic Workforce Builder Pack
by John Barros
Architects human-supervised local AI operations with shared memory, SOP playbooks, and strict approval gates.
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See it in action
You say
Design a supervised operations node for a marketing agency. We need roles for Research and Sales. The first workflow is drafting proposals from call notes in Google Drive.
Your agent does
Build Verdict: PLAN_READY Scope: LOCAL_AGENTIC_OPERATIONS_NODE Memory Plan: Define 'Brand Voice' and 'Pricing Tiers' in CLAUDE.md. Roles:
- Research: Tool access to G-Drive (Read-only).
- Sales: Draft-only permission for Gmail. Governance: Human must approve all proposal drafts before export.
What you get
About this skill
The problem
SMB owners and agency founders often face a "blank page" problem when trying to move from manual tasks to agentic workflows. They lack the structured business memory, SOP mapping, and governance guardrails required to safely delegate operations to local AI agents.
What it does
- Generates a structured
CLAUDE.mdor global memory file containing business identity, pricing, and "never-do" rules. - Converts messy manual SOPs into executable markdown playbooks with clear triggers, procedures, and output contracts.
- Defines specialized department roles (Sales, Research, Content, Ops) with narrow tool scopes and escalation paths.
- Maps local tool connectors for Gmail, Notion, Slack, and Google Drive with explicit read/write/draft permission boundaries.
- Builds a governance model requiring human approval for client-facing messages, financial actions, and destructive file operations.
Why this beats prompting it yourself
Most DIY prompts result in "context bloat" where a single agent tries to do everything, leading to hallucinations and security risks. This skill enforces a modular architecture with multi-run validation gates and strict approval loops that prevent unsupervised execution.
Use cases
- Automating proposal drafting from discovery call notes stored in Google Drive.
- Standardizing weekly client reporting by pulling data from Notion and Sheets.
- Building a content research agent that operates within specific tone-of-voice and brand guidelines.
- Scaffolding a local operations node to handle repetitive admin tasks without giving up final sign-off.
Known limitations
Requires three successful manual validation runs before any workflow can be scheduled for recurring execution. Does not support unsupervised financial transactions or direct client sends without human review.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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