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offer-appointment

Lets your agent record job offers. It tracks details like candidate, position, salary, and dates to manage the hiring process.

What it does

This tool helps record and track new employee hiring information. It creates a formal record for each job offer, including details like salary, dates, and who approved it.

When to use it

  • ✓To log a job offer letter.
  • ✓To create a hiring offer database.
  • ✓To keep a record of new hires.

Example of what to ask your AI

“I want to log a new job offer with salary, dates, and approver details.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/offer-appointment/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/offer-appointment/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

The AI collects essential job offer information, like salary and dates. It then organizes this data so you can easily track hires.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add sickn33/agentic-awesome-skills --skill offer-appointment

Or download just the file:

curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/offer-appointment/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

Offer & Appointment

What it is: Formal hiring record.

Overview

Works out the smallest useful Offer & Appointment setup for the business in front of it, then builds it only when asked. The default output is a short recommendation, not a spreadsheet. Artifacts - CSV, SQL DDL, JSON Schema, Notion mapping - are produced on request, from one field list so they cannot drift apart.

Layer: Layer 3: Onboard. Fits: Growth stage. Table code: n/a.

When to Use This Skill

  • offer letter tracker
  • appointment letter record
  • hiring offer database
  • new hire offer log

Also use it when the user says "formal hiring record", or describes the same process happening in a spreadsheet, a document or someone inboxes.

Do not use it for: payroll calculation, tax filing, or legal advice. This skill produces empty templates only - it never holds or processes real employee or customer data.

How It Works

Follow the shared execution contract. The module-specific rules below define only domain fields, decisions, calculations, and safety constraints.

Step 1 - Identify intent

Read the request and pick the intent before asking anything.

  • "set up" or "build" or "create" -> the user wants artifacts; go to Step 2.
  • "our process is ..." or "it is in a sheet" -> the user wants to move an existing process; capture it, then Step 2.
  • "is this right" or "review" or "audit" -> the user wants a check, not a build; answer from what they share.
  • "how do I ..." -> advice question; answer directly and offer the build only if it helps.

Ask only if this is the highest-value missing fact; otherwise proceed without an opener:

Q: How many offers do you make a month?

Step 2 - Ask only what is missing

Skip anything the user already answered, in any earlier message. Ask the rest one at a time, and stop as soon as the remaining answers would not change the output.

  • Offer - How many offers? / Fixed or variable pay? / Any equity?
  • Terms - Probation length? / Notice period? / Joining date fixed?
  • Process - Who approves? / Signed how? / Template or custom?
  • Current process - How are offers sent? / Docs or email? / Where stored?
  • Outcome - What do you need? / A record, a template or both?

Never invent an answer. If the user does not know, record it as unknown and carry on.

Step 3 - Hold the internal context

Hold the answers in this shape. It stays internal - it is not shown to the user unless they ask, and it never carries a value the user did not give.

module: offer-appointment
intent: null            # setup | advice | review | fix | build | convert | export
scale: null             # Starter | Growth | Scale, only if the answer changes it
areas:
  "Offer": null
  "Terms": null
  "Process": null
  "Current process": null
  "Outcome": null
requested_outputs: []   # csv | sql | json | notion | xlsx - requested formats only
confirmed_facts: []     # only what the user actually said
open_questions: []      # the unanswered ones, in the order worth asking

Step 4 - Recommend the smallest workflow

If an artifact was requested, build it after resolving essential missing facts. Otherwise give a short recommendation and offer the relevant artifact.

Recommended approach: Store the offer as a record with version, approver and expiry. The template is secondary; the record is what you lose today.

Why this one: Offer data is the bridge between recruiting and payroll. Capturing it once, at offer stage, prevents re-keying at joining.

Workflow: Approved offer → Offer sent → Candidate accepts → Record created → Onboarding started

Step 5 - Build only on request

Once the user asks for it, derive the fields from the confirmed context and emit the requested artifacts. For machine-readable text, keep prose outside the data; for files, provide a usable link. Report material validation failures or limitations separately.

A selected Notion output is rendered by notion-manual-import, so route the Notion step there. When the user selects Notion, hand that step to ](https://github.com/sickn33/agentic-awesome-skills/blob/main/skills/notion-manual-import/SKILL.md): it holds the CSV, the property mapping, the import steps and the verification checklist, and it renders the Field Reference below instead of defining a table of its own. Do not restate the mapping here and do not improvise the import steps. Manual CSV and mapping outputs need no

…

FAQ

What are artifacts like CSV or SQL for?

These are file formats you can request to organize and analyze offer data outside the AI, for example, in a spreadsheet or database.

Can the AI calculate taxes or give legal advice?

No, this tool is only for recording and tracking job offers. It does not handle complex financial calculations or legal advice.

What if I don't know some information?

The AI will record the information as 'unknown' and continue. It does not invent data you haven't provided.

Details

Original description by the author

Offer register: candidate, position, department, employment type, offered salary and currency, offer date and expiry, joining date, probation, approver and sign-off. Use for offer tracking.

repo: sickn33/agentic-awesome-skills

Popularity

GitHub stars
48k
Ranking position
#3745
License
MIT
Updated
10/15/2026

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