onboarding

A framework for welcoming new employees and planning their first 30, 60, and 90 days. It includes setup tasks, training, meetings, goals, activities, success measures, and feedback.

In plain words
What is it for?
Preparing onboarding plans, assigning early activities, scheduling introductions, tracking training, setting initial goals, and improving the onboarding experience.
Why use it?
It gives new hires and their managers a shared plan for learning the organization, starting useful work, and checking progress.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/saolalab/clawforce/onboarding
Any agent
npx skills add saolalab/clawforce --skill onboarding
Clone the repo
git clone --depth 1 https://github.com/saolalab/clawforce

Made for: Claude Code, Codex.

Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,595 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00044 $0.01595
Opus 5 $0.00022 $0.00797
Sonnet 5 $0.00009 $0.00319
Haiku 4.5 $0.00004 $0.00160

Measured 2d ago against content hash 9422305620bf, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

onboarding scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

marketplace/roles/hr-manager/workspace/skills/onboarding/SKILL.md · 237 lines

How it starts

The opening of the file, as written. The whole thing — 237 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Onboarding

30-60-90 Day Plan Template

# 30-60-90 Day Plan: {Employee Name} — {Role}

## First 30 Days: Learn & Observe

### Goals
- {Goal 1: Understand company culture and values}
- {Goal 2: Learn key systems and tools}
- {Goal 3: Meet team members and stakeholders}
- {Goal 4: Complete initial training modules}

### Key Activities
- [ ] Complete HR paperwork and account setup
- [ ] Attend company orientation session
- [ ] Meet with manager for role expectations
- [ ] Review key documentation and processes
- [ ] Shadow team members on key workflows

### Success Metrics
- {Metric 1: e.g., "Complete all required training"}
- {Metric 2: e.g., "Have 1:1s with all team members"}

## Days 31-60: Contribute & Build

### Goals
- {Goal 1: Start contributing to team projects}
- {Goal 2: Build relationships across departments}
- {Goal 3: Identify areas for improvement}
- {Goal 4: Take ownership of first project}

### Key Activities
- [ ] Lead first project or initiative
- [ ] Participate in team meetings and planning
- [ ] Provide feedback on processes
- [ ] Attend relevant training or workshops
- [ ] Set up regular 1:1s with manager

### Success Metrics
- {Metric 1: e.g., "Complete first project deliverable"}
- {Metric 2: e.g., "Receive positive feedback from stakeholders"}

## Days 61-90: Excel & Innovate

### Goals
- {Goal 1: Demonstrate full competency in role}
- {Goal 2: Propose and implement improvements}
- {Goal 3: Mentor or support other team members}
- {Goal 4: Set goals for next quarter}

### Key Activities
- [ ] Take on more complex projects
- [ ] Propose process improvements
- [ ] Contribute to team knowledge sharing
- [ ] Complete 90-day review with manager
- [ ] Set development goals for next quarter

### Success Metrics
- {Metric 1: e.g., "Meet or exceed role expectations"}
- {Metric 2: e.g., "Receive recognition from peers"}

First Week Checklist

Pre-Start (HR Prep)

  • Send welcome email with first day details
  • Prepare equipment (laptop, access cards, etc.)
  • Set up accounts (email, Slack, HRIS, etc.)
  • Assign buddy
  • Schedule orientation sessions

Read the full file on GitHub · 237 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 237 lines · 44 tokens per session scan A 9422305620bf

Subscribe to this mod's changes

onboarding is a skill published in the GitHub repository saolalab/clawforce (38 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 44 tokens to every session and 1,595 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

agenticmail

🎀 AgenticMail — Full email, SMS, storage & multi-agent coordination for AI agents. 63 tools.

InternLM/WildClawBench · 28 tokens

ai-meeting-scheduling

Booking links fail for groups. SkipUp schedules meetings with 2-50 participants via email — one API call coordinates across timezones automatically. Also: check status, pause, resume, or cancel requests. Async only — does not instant-book, access calendars, or do free/busy lookups.

InternLM/WildClawBench · 66 tokens

agentic-paper-digest-skill

Fetches and summarizes recent arXiv and Hugging Face papers with Agentic Paper Digest. Use when the user wants a paper digest, a JSON feed of recent papers, or to run the arXiv/HF pipeline.

InternLM/WildClawBench · 54 tokens

eachlabs-voice-audio

Text-to-speech, speech-to-text, voice conversion, and audio processing using EachLabs AI models. Supports ElevenLabs TTS, Whisper transcription with diarization, and RVC voice conversion. Use when the user needs TTS, transcription, or voice conversion.

InternLM/WildClawBench · 60 tokens

arxiv-summarizer-orchestrator

End-to-end orchestration skill for periodic arXiv collection and reporting using three sub-skills: arxiv-search-collector, arxiv-paper-processor, and arxiv-batch-reporter. Supports manual language control across all markdown outputs and Stage-B processing strategy (subagentparallel default max 5, or serial).

InternLM/WildClawBench · 75 tokens

academic-literature-search

这是一个专注于学术文献检索的专业工具,集成了多个权威学术数据库,提供全面、快速、准确的文献检索服务。支持多数据库并发检索、高级过滤、智能排序和多种输出格式。.

InternLM/WildClawBench · 0 tokens