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AgentHandover

What if OpenClaw, Claude Code, Codex etc. knew how to do your work without you saying it? AgentHandover observes you, learns and teaches your agents with self-improving skills.

Install / Use

npx skills add sandroandric/AgentHandover

Installs into whichever agent you are using.

About this skill

Quality Score

0/100

Supported Platforms

Claude Code
Claude Desktop
OpenAI Codex

README

<p align="center"> <sub>Created by Sandro Andric</sub> <br/> <a href="https://www.sandric.co/"><img src="resources/sandric-wordmark.png" width="120" alt="sandric — Product Studio by Sandro Andric" /></a> </p> <p align="center"> <img src="resources/favicon.png" width="140" alt="AgentHandover" /> </p> <h1 align="center">AgentHandover</h1> <p align="center"> <strong>Work once. Hand over forever.</strong> </p> <p align="center"> <a href="https://github.com/sandroandric/AgentHandover/releases/latest"><img alt="Latest release" src="https://img.shields.io/github/v/release/sandroandric/AgentHandover?label=release&color=blue" /></a> <img alt="License" src="https://img.shields.io/github/license/sandroandric/AgentHandover?color=blue" /> <img alt="Platform" src="https://img.shields.io/badge/platform-macOS-black" /> <img alt="Local-first" src="https://img.shields.io/badge/local--first-yes-brightgreen" /> <a href="https://discord.gg/Fcx3X7CtBV"><img alt="Discord" src="https://img.shields.io/badge/discord-join-5865F2?logo=discord&logoColor=white" /></a> </p> <p align="center"> <a href="#demo">Demo</a> &middot; <a href="#quickstart">Quickstart</a> &middot; <a href="#what-you-can-automate">Use Cases</a> &middot; <a href="#what-a-skill-looks-like">What a Skill Looks Like</a> &middot; <a href="#how-it-works">How It Works</a> &middot; <a href="#connect-your-agent">Connect Your Agent</a> &middot; <a href="#install">Install</a> &middot; <a href="#privacy">Privacy</a> &middot; <a href="#contact">Contact</a> </p>
<p align="center"> <img src="AgentHandover.png" alt="The Struggle - The Discovery - The Transformation" /> </p>

Demo

<p align="center"> <a href="https://youtu.be/29YzD88y-f4"> <img src="https://img.youtube.com/vi/29YzD88y-f4/maxresdefault.jpg" alt="AgentHandover — New demo" width="600" /> </a> </p> <p align="center"><a href="https://youtu.be/29YzD88y-f4"><strong>New demo</strong></a> &middot; <a href="https://youtu.be/3nGH3rYbgfY">Original demo</a></p>

Show it once. Hand it off forever.

AgentHandover watches how you work on your Mac, turns your workflows into reusable Skills, and lets agents like Claude Code, OpenClaw, Hermes, Codex, or any MCP-compatible tool execute them the way you do it.

Each Skill captures the what, the why, and the how — steps, strategy, decision logic, guardrails, and your writing voice. And they're self-improving: agents report back after every execution, successes boost confidence, deviations become new decision branches, failures trigger corrections.

You already know how to do your work. Now your agents can too.

Why this matters

Getting an AI agent to do real work today means writing prompts or hand-crafting skills — brittle, time-consuming, and stale the moment your process changes. Worse, those skills capture what you do, not how you decide.

AgentHandover flips it. Instead of telling the agent how you work, you just work. The system watches, infers the strategy behind your clicks, and produces Skills with the why built in — selection criteria, guardrails, decision branches, your voice. Because agents report back after every execution, Skills get better the more they're used.

Less time writing prompts. More time doing work that matters.

What you can automate

AgentHandover learns whatever you do repeatedly on your Mac. A few examples of the kinds of workflows it handles well:

  • Research routines — Your way of scanning sources, extracting key facts, and composing a summary.
  • Community engagement — Daily check-ins on Reddit, Discord, or forums with your selection rules and voice.
  • Support triage — How you read a ticket, check the dashboard, pick a macro, and draft a reply.
  • Data extraction — Pulling structured data from a dashboard, CRM, or spreadsheet the way you do it.
  • Ops checklists — Deploys, releases, status updates — your actual sequence with the decisions you make.
  • Personal skill library — Any repetitive workflow you don't want to explain to an agent twice.

If it's a workflow you've done three times and will do again, it belongs in a Skill.

Quickstart

  1. Install. Download the latest .pkg from Releases and double-click. The onboarding app walks you through permissions and auto-downloads the best AI model for your Mac.
  2. Record a task. Click Record in the menu bar, name it (e.g. "Daily Reddit marketing"), perform it once, click Stop.
  3. Answer 1-3 questions. AgentHandover asks from the agent's perspective — "What determines which posts you engage with?"
  4. Review and approve. Open the Skill in the menu bar app, check the steps/strategy/guardrails, click Approve for Agents.
  5. Connect your agent. agenthandover connect claude-code (or codex / openclaw). One command.
  6. Run it. In Claude Code, type /ah-reddit-community-marketing. The agent executes your workflow.

That's the whole loop. Record once, hand off forever.

What a Skill Looks Like

Here's an illustrative example of what a Skill looks like:

Reddit Community Marketing
Daily engagement workflow - 6 steps - 4 sessions learned

STRATEGY
Browse target subreddits for posts about marketing tools or growth
hacking. Engage with high-signal posts (10+ comments, posted within
48h, not promotional). Write authentic replies that acknowledge the
problem, share personal experience, and softly mention the product.

STEPS
1. Open Reddit and navigate to r/startups
2. Scan posts - skip promotional, skip < 10 comments
3. Open high-signal post and read top comments
4. Write reply: acknowledge -> experience -> mention product
5. Submit and verify not auto-removed
6. Repeat for r/marketing, r/growthacking (max 5/day)

SELECTION CRITERIA              GUARDRAILS
- Posts with 10+ comments       - Max 5 replies per day
- Not promotional or competitor - Never identical phrasing
- Posted within 48 hours        - Never reply to own posts
- Relevant to [product category]- Empathy-first tone always

VOICE & STYLE
Tone: casual | Sentences: short and punchy | Uses emoji
> Hey great point about the engagement metrics! We should
> def try that approach with the subreddit

~15 min daily - 9-10am                     Confidence: 89%

Skills follow the same format as Claude Code's native skills -- same frontmatter, same markdown structure -- but go further. Hand-written skills say "do X then Y." AgentHandover Skills include the strategy behind the steps, selection criteria, guardrails, your voice, and evidence-backed confidence from real observations. No hand-written skill has that.

How It Works

Two ways to teach

Focus Recording -- Click Record in the menu bar, name the task, perform it, click Stop. AgentHandover asks 1-3 targeted questions from the agent's perspective ("What determines which posts you engage with vs. skip?"), then generates a complete Skill. Best for workflows you want to hand off right now.

Passive Discovery -- Just work normally. AgentHandover recognizes recurring workflows across sessions using semantic similarity, accumulates observations, and when it has enough evidence, runs behavioral analysis to extract the strategy, decisions, and patterns behind your actions -- then generates a Skill automatically. You don't have to do anything.

You stay in control

Every Skill starts as a draft in your menu bar app. Six gates must pass before an agent can execute:

| Gate | What it checks | |------|---------------| | Lifecycle | You reviewed and promoted it through each stage (Observed > Draft > Reviewed > Verified > Agent Ready) | | Trust | You authorized the agent to execute, not just observe | | Freshness | The Skill was observed recently -- stale Skills auto-demote | | Preflight | Required apps are running, no blocked domains | | Evidence | Enough observations, high confidence, no contradictions | | Execution history | Past success rate -- 3+ failures auto-demote |

The system suggests promotions based on evidence. You decide.

The Knowledge Base

Everything AgentHandover learns lives in a local knowledge base on your machine. It's not a flat list of files -- it's an active intelligence layer that gets smarter the more you work.

Vector store -- Every observation is embedded (nomic-embed-text, 768d) so the system finds similar workflows by meaning, deduplicates Skills that describe the same task differently, and links activity across sessions. Optional image embeddings (SigLIP, 1152d) capture what your screen looked like.

Voice profiles -- Your writing style accumulates per workflow and strengthens over sessions. One reply is a guess. Twenty replies is a fingerprint the agent can match. Casual on Reddit, formal in client emails -- the system knows the difference.

User profile -- Aggregated across all workflows: your tools, working hours, communication patterns, and overall writing style. Agents read this to adapt to you.

Semantic search -- Agents can search the knowledge base by meaning via the MCP server or REST API. "Find something about deploying" returns your staging deployment Skill even if it's titled "Push to Prod."

Execution Feedback Loop

Most tools stop at "here's a procedure, good luck." AgentHandover closes the loop. When an agent executes a Skill, it reports back what happened -- and the Skill gets better.

How it works: Every Skill includes an execution protocol. The agent calls report_execution_start before beginning, report_step_result after each step, and report_execution_complete when done. AgentHandover processes the results:

  • Success -- Confidence goes up. Freshness confirmed. Timing updated via exponential moving average.
  • Deviation -- The system tracks what the agent actually did vs. what was expected. After 2+ deviations on the same step, it suggests a decision branch.

Related Skills

View on GitHub
GitHub Stars680
CategoryDevelopment
Updated20h ago
Forks53

Languages

Python

Security Score

95/100

Audited on Aug 7, 2026

No findings