AI LinkedIn Recommendation Generator
Write genuine LinkedIn recommendations fast
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Has a former colleague asked you for a recommendation and you have been avoiding it for a fortnight? Do you genuinely rate someone and still find the blank box impossible? Have you ever written one that came out as three sentences of adjectives with nothing underneath them?
Recommendations are among the most useful things you can do for someone and among the most postponed. Not because people are unwilling, but because praising a colleague in public, in writing, is a peculiar kind of hard. The AI LinkedIn Recommendation Generator gives you a structured draft so the job becomes editing rather than starting.
Short answer: The AI LinkedIn Recommendation Generator is a free tool that drafts a LinkedIn recommendation for a colleague, employee or client. You supply who they are and what they actually did, set the tone, length and level of personalisation, and it returns a draft you edit into something you can honestly sign.
What is AI LinkedIn Recommendation Generator?
It writes the recommendation text that appears on someone else's profile, attributed to you.
You describe the person, your working relationship and what they actually did, and it returns a structured draft. Your name sits on the finished version, which shapes everything about how you should use it.
One practical note about the interface. This page shares its options panel with the outreach tools on the site, so the controls are labelled Message Goal, Include Greeting and so on. They work here, they just use the vocabulary of sending a message. The prompt placeholder mentions contacting someone for the same reason. Ignore the wording and use the settings as described below.
Avoid A recommendation is a public statement of fact about a real person, permanently attached to your name and theirs. Anything generated here about their achievements, their results or their character is invention until you confirm it. Never publish praise for work you did not personally witness. Use the draft for structure, and replace every claim with something you would repeat in a reference call.
Why Use AI LinkedIn Recommendation Generator?
Because the barrier is structure, not goodwill. Most people know exactly why someone was good and cannot get it into a paragraph.
| The problem | What usually gets written | What a draft gives you |
|---|---|---|
| You rate them but cannot say why | Hardworking, reliable, a pleasure to work with | A shape that asks for a specific situation instead |
| You worked together years ago | Nothing, because the details have faded | Prompts that pull out what you do still remember |
| It has been sitting in your inbox | An apology three weeks later | A draft in one pass, edited in ten minutes |
| You want it to sound sincere | Formal language that reads as a template | A conversational register you can make your own |
Who Should Use It?
- Managers writing for people who reported to them, especially after a redundancy
- Colleagues returning a recommendation somebody wrote for them
- Clients who want to vouch for a freelancer and never find the time
- Freelancers recommending a subcontractor they would use again
- Anyone with a request that has been sitting unanswered out of guilt
How Does AI LinkedIn Recommendation Generator Work?
The page uses the working surface shared across every tool on the site.
- Prompt input area. A large box whose placeholder reads Enter who you're contacting and why…, shared with the outreach tools. Here, put who the person is, how you worked together, and what they actually did.
- AI model selector. Choose the engine before generating, from MSB AI, OpenAI ChatGPT, Google Gemini, Anthropic Claude AI, xAI Grok AI, DeepSeek, Qwen, Meta AI, NVIDIA AI, OpenRouter AI and MiniMax.
- Advanced options accordion. Closed until opened, holding the ten controls covered below.
- Generate button. Sends your context, engine and settings through the prompt engineering layer, the wrapper of instructions the site adds around your text.
- Output section. The draft lands in the result card with a live word count in the footer.
- Export tools. DOC, TXT and HTML downloads sit under the card, useful when you want to check the wording with the person before posting it.
- Activity history panel. Earlier drafts stack below with copy, listen, reuse, download and open result, which helps if you are writing several after a team change.
Tip Before you generate anything, write down one moment. A specific project, a problem they solved, a thing they did when it would have been easier not to. One remembered moment produces a better recommendation than any amount of describing their qualities.
Key Features
Structure without the blank page
The draft arrives with a beginning, a middle and a close, which is the part most people cannot get past on their own.
Detail led rather than adjective led
High personalisation pushes the draft to use the specifics you supplied instead of a list of positive words.
Warmth you can set
Tone options from Respectful to Warm let the register match the relationship rather than defaulting to formal.
Length that suits the ask
Message Length scales from a couple of lines for a brief endorsement to a fuller piece for a former direct report.
Easy to check first
Export the draft and send it over before publishing, which most people appreciate more than a surprise.
Best Use Cases
- Writing for a colleague made redundant, where speed genuinely matters
- Recommending a freelancer or contractor you would hire again
- Returning a recommendation someone wrote for you
- Endorsing a former direct report applying for their next role
- Vouching for someone whose work you know well but whose job title you never learned
- Clearing a request that has been sitting in your inbox for a month
Advanced Options Guide
Ten real controls, none preselected. The labels come from the shared outreach panel, so here is what each one does for a recommendation.
| Option | What it controls | When to change it | Where to start |
|---|---|---|---|
| Message Goal | The purpose: Connect, Collaborate, Pitch, Network, Sell, Recruit, Follow-Up or Appreciate | Only change it if you are writing something other than a recommendation | Appreciate. It is the one option on this list that matches the job |
| Tone | The voice: Professional, Friendly, Warm, Confident, Respectful, Persuasive, Casual or Concise | Avoid Persuasive, which turns a recommendation into a sales pitch | Warm for a close colleague, Professional for a client relationship |
| Message Length | The size: Short, Normal or Detailed | Detailed for someone you managed directly for years | Normal. Two solid paragraphs outperform a page of praise |
| Personalization | How tailored: High, Medium, Low or Template | Never use Template for a named person's public profile | High. A generic recommendation helps nobody and reflects on you |
| Include Greeting | Opens with a salutation | Turn it off. Recommendations are not addressed to the reader | Off. A greeting reads as a letter pasted into the wrong field |
| Include CTA | Adds a closing ask | Off, unless you genuinely want to invite approaches | Off. A recommendation is a statement, not a request |
| Add a Compliment | Adds explicit praise | On here, since praise is the point, provided it stays specific | On, but check every line is something you actually observed |
| Add Value Hook | Leads with what makes them useful to others | On when the recommendation is aimed at future employers | On. It shifts the focus from your opinion to their usefulness |
| Personalization Depth | Slider from 1 to 100, controlling how hard it works your details in | Raise it whenever you have supplied a real example | Around 80, since specifics are the entire value here |
| Custom Instructions | Free text up to 1000 characters | Every run. This is where your remembered detail goes | The specific project and outcome, plus: only use facts I have given |
Example Outputs
Ellen managed a junior developer for two years and has been asked for a recommendation. She opens the AI LinkedIn Recommendation Generator with this.
Writing for Sam Whitfield, junior developer, reported
to me for two years at a logistics software company.
The thing I remember: our overnight batch job kept
failing and nobody could reproduce it. Sam spent three
evenings reading logs and found it was a timezone
issue on one server. Nobody asked him to.
Message Goal = Appreciate
Tone = Warm
Message Length = Normal
Personalization = High
Include Greeting = Off
Include CTA = Off
Add a Compliment = On
Add Value Hook = On
Personalization Depth = 80
Custom Instructions = Use only the facts I have given.
Do not invent projects, metrics or job titles. Do not
say he is a team player.Sam reported to me for two years, and the thing I
would tell any hiring manager is how he handled a
problem nobody had assigned him.
Our overnight batch job had been failing intermittently
for weeks. Sam spent three evenings going through logs
on his own initiative and traced it to a timezone
setting on a single server…One remembered evening does more than a paragraph of adjectives. The instruction to use only supplied facts is what kept a fictional performance metric out of it, and the ban on "team player" removed the phrase that makes recommendations interchangeable.
Caution Watch for job titles, dates, team sizes and results appearing in the draft that you never supplied. These read as harmless detail and are the most likely thing to be wrong. Delete anything you cannot personally confirm.
- ✅ Write down one specific moment before you generate
- ✅ Set Message Goal to Appreciate and Include Greeting off
- ✅ Instruct it to use only the facts you supplied
- ✅ Delete every claim you did not personally witness
- ✅ Send the draft to the person before you publish it
What works well
- Removes the structural barrier that leaves requests unanswered
- High personalisation turns one remembered moment into a paragraph
- Banned phrases keep the generic language out
- Free to use, with no account needed
What to watch for
- It will invent titles, dates and results that look entirely credible
- The panel labels come from the outreach tools and read oddly here
- An unedited draft praises qualities you may never have seen
- Your name goes on the result, so the checking is not optional
Comparison Table
| Approach | What you get | Where it falls down |
|---|---|---|
| Never getting round to it | Nothing to check or regret | You let down someone who asked you for a favour |
| Three lines of adjectives | Done in two minutes | Interchangeable with every other recommendation on their profile |
| Asking them to draft it for you | Accurate, and no writing required | Awkward to ask, and it ends up in their voice rather than yours |
| AI LinkedIn Recommendation Generator | A structured draft built around your real example | Every claim needs verifying before your name goes on it |
AIToolsay is a free AI tools platform. The AI LinkedIn Recommendation Generator is one workspace in a large library, each tool built for a single job and each carrying its own options panel with its own prompt engineering behind it. Nothing needs registering for and nothing needs installing. A selector at the top decides which engine writes for you, spanning MSB AI, OpenAI ChatGPT, Google Gemini, Anthropic Claude AI and several more, so a draft that reads stiffly is one click from a warmer one. Asking for a recommendation is its own small piece of writing, which the AI LinkedIn Connection Message Generator handles. Everything else is reachable from the AIToolsay homepage.
Frequently Asked Questions
Is it dishonest to use the AI LinkedIn Recommendation Generator?
Not if the facts are yours. Using it for structure while supplying the real examples is no different from using a template. Publishing praise for things you never saw is the line, and it is a clear one.
Is the AI LinkedIn Recommendation Generator free?
Yes, and no account is needed.
Why does the panel talk about messages and greetings?
It shares an options component with the outreach tools. The controls still work, they are just labelled for a different job.
Which Message Goal should I choose?
Appreciate. The other options are built for outreach and will push the draft toward pitching or networking.
How long should a LinkedIn recommendation be?
Two paragraphs is usually right. One specific story plus a sentence on what they would bring to a future employer beats anything longer.
Should I show the person before publishing?
Yes. It costs a message, it catches anything you have misremembered, and most people would rather be asked than surprised.
What if I cannot remember anything specific?
Then say less. A short, honest recommendation about the one thing you do remember is worth more than a long one built on nothing.
A good recommendation is not a list of qualities. It is one story that lets a stranger draw their own conclusion, and the reason so few exist is that finding the story feels harder than writing the adjectives. It is not. It just has to be done before the writing starts.
So open the AI LinkedIn Recommendation Generator, remember the one thing that person did that you still tell people about, and finally answer the request sitting in your inbox. Thanks for reading to the end, and I hope it helps them land the next thing. Should the tool prove useful, the AIToolsay community is open to join, our social accounts announce each new tool, push notifications reach you first, and the newsletter carries guides of this kind.
Let AI Speak.
Sabir
Founder of AIToolsay and a passionate AI enthusiast dedicated to building practical, user-friendly AI tools that simplify everyday tasks.
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