Offer & Rejection Email · Human-Tone Template
Make offer / rejection emails — high-volume HR work — professional yet warm.
Pain addressed · Pain #1: AI-written offers and rejection notes read as 'standard template' — candidates feel coldly handled, your employer brand quietly degrades.
Offer & Rejection Email · Human-Tone Template
You're an HRBP skilled at candidate comms. Write an {email_type} (offer or rejection) that's professional yet warm — even rejected candidates would refer friends.
# Email type
{email_type}
# Candidate
- Name: {candidate_name}
- Position: {position}
- Rounds completed: {rounds_completed}
- Observed strengths: {candidate_highlights}
# (Offer) Details
- Comp: {comp_details}
- Start: {start_date}
- Onboarding: {onboarding_info}
- Our urgency: {urgency_for_us}
# (Rejection) Reasons
- Internal real reason: {real_reason}
- External version: {public_reason}
- Keep in pool? {keep_in_talent_pool}
## Subject (≤ 18 chars)
### Offer
- Not "Job offer letter"
- "{candidate_name}, welcome to {team_name}" or "We'd like to officially invite you"
### Rejection
- Not "Interview result notification"
- "Feedback on your {position} interview + what's next"
## Offer body (≤ 350 words)
### Para 1: Sincere open (≤ 50)
Cite a specific interview observation. Make them know it's not a template.
### Para 2: Formal offer (≤ 80)
Position + base + bonus + start (with specifics), link to letter.
### Para 3: Help them decide (≤ 100)
Anticipate their weighing — offer help (e.g. "30 more min with Tech Lead").
Reply deadline (3-7 days). Flexible start window.
### Para 4: Personal close (≤ 30)
First-person, anticipation, WeChat/phone as backup channel.
## Rejection body (≤ 250)
### Para 1: Direct yet warm (≤ 50)
Lead with the result. Genuine but not overdone.
### Para 2: Feedback (≤ 100)
1-2 specific constructive points based on assessment, not "keep improving".
### Para 3: What's next (≤ 50)
If keeping in pool: explicit re-contact horizon. Else: well-wishes without fake "future opportunities".
### Para 4: Real-person close (≤ 30)
Your name + contact. Cross-company connection welcome.
# Must avoid
- "After careful consideration, we regret..." cliché
- Empty "future opportunities" promise
- "Given your performance..." blame-shifting
- Making them feel like a "failed transaction"Open directly on your favourite AI
One click copies the prompt and opens the platform in a new tab — just paste (⌘/Ctrl + V). Recommended platforms are ordered by content fit.
Workflow · 5 steps
- 1
Send within 24 hours of the decision, offer or rejection. Delays sour the candidate experience.
- 2
For offers: fill in comp details, observed strengths, and your team's actual urgency. Run the prompt.
- 3
For rejections: keep the real internal reason and the external version in separate fields — don't blend them.
- 4
On the first draft, edit three things: add one specific interview observation, cut every other superlative ('amazing', 'incredibly'), and sign with your real name + LinkedIn/Calendly.
- 5
Read it out loud before sending. If it doesn't sound like a real person, rewrite. Checklist must pass.
Verify before you ship
AI's "almost right" is the #1 pain. Tick these off so reviewers can't find the obvious holes. (Checkbox state stays local — we don't track it.)
Why this prompt works
This prompt isn't a generic “write me a Email & Comms Templates”. It folds in the concrete context a HR & Recruiting actually faces (target reader, info density, deliverable format). LLMs deliver an order-of-magnitude better answer when they get role × scenario × constraints together — they can make the right tradeoffs about what to spotlight and what to cut.
When to use
Best moment: you know roughly that you need to do a Email & Comms Templates, but you're stuck on “how do I even ask the AI?” Muscle memory has no template. Copy this card, tweak 2-3 fields per the workflow, and get a first revisable draft in 30 seconds.
Common pitfalls
- Send without tweaking placeholders · the draft reads as default-GPT and your reviewer spots it in 3 seconds.
- Skip the verify checklist · “almost right” failures usually hide in a thing you assumed the model handled but it didn't.
- Stop after the first answer · a single follow-up like “make section X tighter / more formal” usually pushes a 70 → 90.
Variants & extensions
Want to use this card more aggressively? Three extensions:
- Swap languages: both EN/ZH prompts ship in the card — use the EN version when shipping to a Western audience.
- Swap platforms: the same prompt has slightly different taste on ChatGPT / Claude / Kimi. The recommended-platform pill marks the best fit.
- Stack the checklist: paste the verify checklist back into the chat and ask the AI to self-audit — error rate drops sharply.
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