If you give AI a topic and ask it to write a LinkedIn post that leaves out the work that makes the post worth reading: understanding your buyers, finding an interesting angle, pulling together evidence, and knowing what you can credibly say.
These 12 prompts turn that work into a repeatable system, from researching your market to building a content calendar and identifying which posts contribute to real business conversations.
Here's what you'll build:
- A voice guide based on how you actually communicate.
- A research process that finds useful ideas before you need them.
- A draft and review workflow with specific quality standards.
- A reporting loop that helps you decide what to write next.
Gemini CLI runs in your terminal, reads and writes the files in the folder you start it from, and can be scripted, so the whole system ends up as plain files and commands you can rerun every month.
Save this for your next content planning session.
## Before You Run a Single Prompt: Load Your Business Context
Gemini CLI needs more than your job title and a request to "sound human." Give it enough context to understand who you sell to, what you believe, and which claims you can support.
Paste this first:
> Use the following as the working context for my LinkedIn content. Save it in a reference document I can reuse, and tell me where it is stored.
> Business: [Company name, website, product or service, and typical sales cycle].
> Audience: [Buyer roles, company sizes, industries, and locations]. Their main problems are [problems], their common objections are [objections], and the events that make them look for help are [triggers].
> Positioning: We help [audience] achieve [outcome] through [approach]. Our strongest differences are [differences]. We are not a good fit for [disqualifiers].
> Point of view: I believe [three opinions about my industry]. I disagree with [common advice] because [reason].
> Evidence: Use these approved case studies, results, examples, and personal experiences: [sources]. Do not invent customers, revenue figures, stories, or quotations.
> Voice: Here are [10-20 posts] and [transcripts or writing samples] that sound like me. Avoid [phrases, tones, and formatting habits].
> Goals: My primary LinkedIn objective is [qualified conversations / deal support / recruiting / awareness]. My offer is [offer], and the next step I want interested readers to take is [action].
> Working rules: Use connected sources only where access is available and authorized. If a source is inaccessible, ask for an export or pasted material. Keep LinkedIn publishing, comments, connection requests, and messages with me. Draft into [review destination], distinguish evidence from inference, and flag anything that needs my input.
Keep that context current as your offer, audience, and opinions change.
### Where Gemini CLI keeps this context
Gemini CLI loads `GEMINI.md` context files into every session, in layers: `~/.gemini/GEMINI.md` applies to everything you do, a `GEMINI.md` in the project folder (or its `.gemini/` folder) applies to that project, and files in subfolders add more specific instructions on top.
Make a folder just for LinkedIn work, start `gemini` inside it, and ask it to save the answers above as `context/business.md`. Then keep the project `GEMINI.md` short and import the context instead of pasting it:
```
# LinkedIn content workspace
@./context/business.md
@./context/voice-guide.md
Drafts go to drafts/, reviews to reviews/, reports to reports/.
Never publish, comment, connect or message on LinkedIn. Prepare drafts only.
```
The `@` lines pull those files in, so you can edit the business context without touching anything else. Run `/memory show` to see exactly what is loaded, and `/memory refresh` after you change a file. `/memory add` appends a single fact to the global `~/.gemini/GEMINI.md`, it is handy for a small preference, but users report that such facts are not always recalled, so keep anything important in the files you control. If some folders should stay out of reach, such as contracts or billing exports, list them in `.geminiignore`.
Settings follow the same layering as context: `~/.gemini/settings.json` holds your personal defaults, `.gemini/settings.json` inside the folder holds this project's, and a system-wide file managed by an admin overrides both. After all twelve prompts, the folder looks roughly like this:
```
linkedin/
GEMINI.md imports the files in context/
.geminiignore folders the tools must not touch
.gemini/
settings.json project MCP servers
commands/linkedin/calendar.toml
agents/reviewer.md
skills/editorial-review/SKILL.md
context/ business.md, voice-guide.md
samples/ calls/ research/
drafts/ reviews/ inbox/ replies/ reports/
```
One setup note: Google's README says that on June 18, 2026, Gemini CLI was replaced by Antigravity CLI for unpaid-tier and Google One accounts. Gemini CLI keeps working with a Gemini API key, Vertex AI, or an organization's Code Assist license.
## PART 1: RESEARCH + CONTENT PRODUCTION
Prompts 1-8
## 1. Build Your Voice Guide
A useful voice guide should explain the choices behind your writing, including how you introduce an argument, use examples, and move between ideas.
"Conversational and authoritative" won't get you very far.
> Analyze my supplied posts and transcripts to build a practical LinkedIn voice guide.
> Identify:
> How I open posts, explain ideas, and close an argument.
> My usual vocabulary, sentence lengths, paragraph lengths, and use of lists.
> How I express disagreement, uncertainty, humor, and confidence.
> Phrases I use naturally, with verbatim examples and source references.
> Writing habits that appear in weaker examples but should not become rules.
> Create a list of phrases and patterns to avoid, including unnecessary repetition, manufactured drama, unsupported certainty, and excessive one-line paragraphs.
> Finish with three before-and-after examples showing how you would edit generic copy into my voice without changing its meaning. Keep the guide specific enough that another writer could apply it.
**In Gemini CLI:** put the sample posts in `samples/` and add the folder to the prompt with `@samples/`. The file tools read more than text: PDFs, images and audio go in as they are, so a recorded talk or a slide deck can sit next to the posts. Your personal writing habits that apply everywhere, not just to LinkedIn, belong in the global `~/.gemini/GEMINI.md`, some writers keep a separate global file for creative work and swap it in. Ask for the result as `context/voice-guide.md`, the import line in `GEMINI.md` already references that file, so after `/memory refresh` every new draft starts from it. `/init` can generate a `GEMINI.md` too, but it is built around code projects, for a writing folder, the short file above is quicker to write by hand.
**Why this matters:** A good voice guide makes feedback reusable. Instead of correcting the same phrasing every week, you can improve the instructions that shape every draft.
## 2. Find the Buyer Questions Worth Answering
Your sales calls and customer conversations can reveal questions that never show up in a keyword tool. The useful ones usually involve a decision someone is struggling to make.
> Review the supplied sales calls, support conversations, customer interviews, and closed-lost notes from [period].
> Group recurring questions into:
> Problems buyers are trying to understand.
> Concerns that delay a decision.
> Alternatives they are comparing.
> Expectations that lead to disappointment.
> Questions they ask right before they decide.
> For each theme, include an anonymized quotation, source reference, number of distinct conversations where it appears, buyer role, and stage in their decision.
> Suggest two LinkedIn angles per theme: one that helps the reader diagnose the problem and one that helps them evaluate a solution. Rank the top 10 by recurrence, commercial relevance, and the strength of our available evidence.
> Separate explicit buyer statements from your interpretation.
**In Gemini CLI:** start the session with `gemini --approval-mode=plan`. Plan Mode keeps the agent to read-only research and planning until you approve, so the first pass over `calls/` proposes the themes without writing anything. Once the grouping looks right, approve it and let the agent write `research/buyer-questions.md`, with the file name and line next to every quotation. Call recordings can go in directly as audio files. Before the second pass, save the session with `/chat save calls-pass1`, so you can return to the approved grouping if the write-up drifts. If a long batch of transcripts fills the session, `/compress` summarizes the conversation so far and frees room for the rest.
**Why this matters:** This gives you a content backlog tied to conversations your business is already having, with language you can recognize and evidence you can check.
## 3. Find Topics Moving From X Into Your Market
A discussion gaining attention on X can become a useful LinkedIn post, provided you explain why it matters to your buyers and contribute something beyond a rewrite.
> Using Google Search grounding, web_fetch for the original pages, and accessible public sources, review the last [seven days] of discussion around [topics] and these accounts: [accounts].
> Find up to 10 developments or arguments relevant to [buyer].
> For each, return:
> The original source, author, publication date, and link.
> A neutral summary of what happened or what is being argued.
> The strongest competing interpretations.
> The practical implication for our audience.
> A possible angle supported by our experience or evidence.
> Label engagement figures as a snapshot, avoid treating popularity as proof, and check factual claims against original sources where possible.
> Recommend three ideas worth developing, explaining what I would need to contribute before each becomes a credible LinkedIn post.
**In Gemini CLI:** the built-in `google_web_search` and `web_fetch` tools do the research, there is no direct X access. Public posts that search engines index can surface, and coverage of them in articles and newsletters usually does, but anything behind a login will not. Paste the posts you care about into `research/x-notes.md` and add `@research/x-notes.md` to the prompt, then ask for the list of URLs it fetched at the end, so you can spot-check the sources. If you scan the same accounts every week, put the prompt in a custom command such as `/research:x` and pass the account list as `{{args}}`.
**Why this matters:** Research gives you a starting point, your judgment gives readers a reason to follow you. A useful adaptation connects the discussion to a decision they actually face.
## 4. Analyze Posts That Outperform Their Authors' Usual Results
Comparing every post with a celebrity account's biggest hit will distort your research. Compare a post with that author's typical results first, then examine what might explain the difference.
> Analyze this supplied LinkedIn swipe file and the available performance data: [file].
> Where enough comparable data exists, compare each post's engagement with the author's median for a similar format and period. Show the calculation and flag small samples, missing metrics, and unusually recent posts.
> For the strongest outliers, identify:
> The topic and intended reader.
> The opening, argument, supporting evidence, and closing.
> The format and approximate length.
> Whether the discussion suggests genuine buyer relevance.
> Possible confounding factors, including a launch, news event, or unusually large distribution.
> Produce five reusable structural patterns, then propose an original idea for each using my own expertise. Do not copy distinctive wording or present an observed pattern as an algorithm rule.
**In Gemini CLI:** reference the export with `@swipe-file.csv` and ask the agent to compute the medians by writing a short script and running it with its shell tool. It asks before running the command, and you end up with a script you can rerun, not a number it estimated. A screenshot of a post's analytics works too: images are a valid input alongside the CSV. To check the columns yourself before the analysis, type `!head -5 swipe-file.csv`: the `!` prefix runs the command in your shell without leaving the session.
**Why this matters:** You get a more useful set of hypotheses to test, while avoiding the assumption that copying a successful post's layout will reproduce its results.
## 5. Turn Recorded Expertise Into Original Posts
A transcript can contain a strong post buried inside a story, an offhand explanation, or a disagreement that deserves more attention than it received in the original conversation.
> Review this interview, podcast, webinar, or meeting transcript: [source].
> Find eight moments that could support an original LinkedIn post. Prioritize decisions, mistakes, surprising observations, practical explanations, and opinions backed by experience.
> For each moment, provide:
> The exact quotation and timestamp or source location.
> The main idea and who would benefit from it.
> Any context needed to avoid misrepresenting the speaker.
> Supporting facts already available.
> One follow-up question that would make the idea stronger.
> Select the three strongest moments and draft a post from each using my voice guide. Preserve the speaker's level of certainty, remove confidential details, and leave placeholders wherever a result or example needs confirmation.
**In Gemini CLI:** the source can be a text transcript or the recording itself, added with `@`. Once you have approved the list of eight moments, save the conversation with `/chat save moments`. If a draft goes sideways, `/chat resume moments` brings you back to the approved list without reading the source again, and `/chat share` exports the session to a Markdown file for your records. For an hour-long recording, ask for a text transcript once and save it next to the audio, later prompts then reuse the file instead of processing the recording again.
**Why this matters:** You can produce content from expertise that already exists without asking someone to manufacture a fresh opinion every time the calendar needs filling.
## 6. Build a Four-Week Content Calendar
A calendar should balance what buyers need to understand with what you have enough evidence to say. Filling every slot with a different version of your offer makes the feed repetitive.
> Build a four-week LinkedIn calendar at [three posts per week] using the approved ideas from our research.
> Include a mix of:
> Practical explanations that help buyers solve a problem.
> Opinions supported by experience or evidence.
> Customer examples we have permission to share.
> Answers to objections and decision questions.
> Occasional offer posts with a relevant next step.
> For each post, specify the reader, single objective, central argument, source material, suggested format, and intended reader action.
> Check for repeated topics, overlapping arguments, unsupported claims, and too many promotional posts. Write full briefs for week one and shorter outlines for weeks two through four.
> Leave room for one timely replacement each week rather than assuming the calendar must remain fixed.
**In Gemini CLI:** this is the prompt worth turning into a custom command, because you will run it every month. Save it as `.gemini/commands/linkedin/calendar.toml`:
```toml
description = "Four-week LinkedIn calendar from approved research"
prompt = """
Build a four-week LinkedIn calendar at {{args}} using the approved ideas in research/.
(the rest of prompt 6)
"""
```
Then `/linkedin:calendar three posts per week` runs it, with your rhythm dropped in where `{{args}}` stands. A `!{ls research/approved}` block inside the prompt runs that command before sending and pastes the current list of approved ideas in, so the command never works from a stale list, Gemini CLI asks you to confirm the shell call first. Pick the slots with the [best time to post on LinkedIn](/tools/linkedin/best-time-to-post) guide.
**Why this matters:** A useful calendar reduces weekly planning work while leaving room for better ideas, new evidence, and changes in the market.
## 7. Draft Posts With Something to Say
The research should determine the argument before Gemini CLI starts polishing sentences. Otherwise, you can end up with clean writing that takes several paragraphs to make an obvious point.
> Write three LinkedIn drafts from these approved briefs: [briefs].
> Use my business context and voice guide. For each draft:
> Make one clear argument for one intended reader.
> Open with a specific observation, tension, result, or question supported by the brief.
> Explain the reasoning with a concrete example.
> Use bullets where they make parallel points easier to scan.
> Vary sentence and paragraph length, allowing occasional one-line emphasis.
> End with a useful implication or natural next step.
> Aim for [180-300 words] unless the idea warrants a different length. Avoid repeated conclusions, invented personal stories, exaggerated promises, and formulaic contrasts.
> Supply two alternative openings and explain briefly how they change the emphasis. Flag missing evidence separately from the publishable copy.
**In Gemini CLI:** ask for each draft in its own file under `drafts/`, and the evidence gaps in a single `drafts/gaps.md`, so nothing unverified hides inside the copy. Start the session with `gemini --checkpointing`: it snapshots the files before every edit, and `/restore` rolls back a rewrite you don't like. Test more openings in the [LinkedIn hook generator](/tools/linkedin/hook-generator), then clean up the line breaks with the [LinkedIn text formatter](/tools/linkedin/text-formatter) and check the length in the [LinkedIn character counter](/tools/linkedin/character-counter). If you prefer to edit in VS Code, the Gemini CLI companion extension shows proposed changes there as diffs, so you accept or reject each edit in the editor.
**Why this matters:** Clear constraints give you drafts that are easier to judge. Your review can focus on the quality of the argument instead of repairing unnecessary filler.
## 8. Create a Separate Editorial Review
Give the reviewer a defined job: find weaknesses in the draft and explain how to fix them. A reassuring "This is strong" is not an editorial process.
> Review these LinkedIn drafts against the brief, source material, business context, and voice guide.
> Score each out of 100 using:
> Buyer relevance: 25.
> Specificity and supporting evidence: 25.
> Strength and clarity of the argument: 20.
> Match with my voice: 20.
> Readability and formatting: 10.
> Show the evidence behind each score. Check every factual claim, identify generic passages, and highlight repetitions, abrupt one-line fragments, and paragraphs that would work better as lists.
> Return a publishable revision, a short explanation of meaningful changes, and any unresolved questions. Treat invented evidence, exposed confidential information, or a misrepresented source as a blocking issue regardless of score.
> Keep everything in the review document for human approval.
**In Gemini CLI:** the reviewer should not remember writing the drafts. Either `/clear` the conversation and load only the briefs, drafts and sources, or define a reviewer subagent in `.gemini/agents/reviewer.md` with the rubric as its instructions and call it for every batch. Keep the output in `reviews/`. Before you publish, run the approved version through the [LinkedIn post analyzer](/tools/linkedin/post-analyzer) as an outside check. A third option is a skill in `.gemini/skills/editorial-review/SKILL.md`: skills load on demand, only when the agent activates them, so the rubric stays out of sessions that do not need it.
**Why this matters:** A review rubric makes your standards explicit. The score helps organize feedback, while the source checks and editor's judgment determine whether the post is ready.
## The first hour after you publish
Once prompt 8 gives you a revision you are happy with, you publish it, and the writing part is done. What comes next is no different from any other MAXXING playbook: the post needs as many reactions as possible during its first hour, the golden hour.
**Your own circle comes first.** The best people to ask for reactions are the ones you can reach directly: coworkers, friends, family, clients. Message them the link right after it goes live.
**No circle to ask? Then a specialised service, as long as its engagement is quality and moderated.** Right after this section is the list of groups we checked for our other articles.
**Our own service for this is aaas.market:**
- real people take part,
- moderation is at the highest level and the audience is the highest quality, because that is where most of the attention goes,
- membership is closed and starts with a verification step,
- every type of engagement is supported.
Start free on aaas.market
**Gemini CLI needs MCP for this.** An agent can only get engagement through MCP. aaas.market's server lives at ` once it is connected, Gemini CLI can ask for any type of engagement on a post that is already live. Publishing, commenting, connection requests and messages remain your job.
Add it once from your shell, outside the interactive session:
```
gemini mcp add --scope user --transport http aaas.market
```
`--transport http` marks it as a remote streaming server, and `--scope user` makes it available in every folder, not just the current one. If you prefer to edit the file, this is the same entry in `~/.gemini/settings.json`:
```json
{
"mcpServers": {
"aaas.market": {
"httpUrl": ""
}
}
}
```
Use `httpUrl`, not `url`: in Gemini CLI, `url` is reserved for SSE servers. Settings are read at startup, so restart `gemini`. The server uses OAuth: on the first connection it answers that you need to sign in, Gemini CLI discovers the sign-in on its own and opens an aaas.market sign-in page in your browser, and the token is stored for later sessions. If the window closes or the token expires, `/mcp auth aaas.market` runs the sign-in again. Then run `/mcp` and check that `aaas.market` shows as connected and lists its tools.
Leave `trust` at its default, `false`, so Gemini CLI asks before each call. Use hyphens rather than underscores in the server name: Gemini CLI names each tool `mcp_{server}_{tool}`, and underscores in the server part blur that boundary.
From then on the step is one sentence. Right after publishing, type: "Request engagement on [post URL] through aaas.market." Gemini CLI shows the call it wants to make, and you confirm it.
## LinkedIn engagement groups you can join
We checked these free communities on Oct 21, 2026, the member counts are the numbers each platform displayed that day. Every group has its own admins and house rules, so read the pinned message before you share your first link.
| Group | Platform | Members | Language | Best for |
|---|---|---|---|---|
| [LinkedIn Engagement Pod & Group](https://t.me/linkedin_engagement_pod) | Telegram | 1,833 members | en | general LinkedIn engagement pod (likes + comments) |
| [LinkedIn Engagement Pod (RVision Digital)](https://t.me/linkedinengagementpod) | Telegram | 1,064 members | en | share posts for likes/comments, connections, skill endorsements |
| [Linkedin engagement pod](https://t.me/linkedinpod1) | Telegram | 488 members | en | general LinkedIn engagement pod |
| [ Social Linkedin/FB/IG Engagement Pod](https://t.me/socialengagementpod) | Telegram | 77 members | en | LinkedIn pod: react + meaningful comment on last 5 posts before shari... |
| [LinkedIn For Breakfast](https://www.skool.com/linkedin-for-breakfast) | Skool | 6,603 members | en | free LinkedIn community with engagement pods, live events |
| [Linkedin Likes and Engagement](https://t.me/linkedinlikesandengagement) | Telegram | 697 members | en | likes/engagement exchange + connections |
| [Linkedin Pod (SF founders like-for-like)](https://chat.whatsapp.com/DBOyIPrDR5IK27yzW606sF) | WhatsApp | n/a (WhatsApp hides count) | en | founders like-for-like on LinkedIn |
| [r/linkedintips](https://www.reddit.com/r/linkedintips/) | Reddit | 38,314 members | en | LinkedIn tips for promoting your brand |
| [LinkedIn Club](https://t.me/linkedinclub) | Telegram | 552 members | en | LinkedIn networking/connections community |
| [r/LinkedInGrowth](https://www.reddit.com/r/LinkedInGrowth/) | Reddit | - | en | LinkedIn growth and connections |
Prefer real engagement without hunting through group chats? Start free on aaas.market.
## PART 2: PIPELINE + PERFORMANCE
Prompts 9-12
## 9. Build Content Around Stalled Deals
Some of your most useful content may answer a concern that several prospects have raised privately. The goal is to explain the issue well enough that future buyers arrive better informed.
> Review the supplied CRM records and call notes for qualified deals that stalled during [period].
> Identify recurring objections and distinguish:
> Explicit objections recorded in conversations.
> Possible explanations that remain unconfirmed.
> Operational delays that content is unlikely to solve.
> For each repeated objection, record the buyer role, deal stage, available evidence, and the question a useful LinkedIn post should answer.
> Recommend five content briefs. Each should explain the concern fairly, show where our approach is appropriate, acknowledge where it is not, and identify the proof required.
> Draft the two strongest posts without naming prospects or revealing deal details. Separately, suggest which approved existing resources a salesperson could share in a relevant conversation.
**In Gemini CLI:** if your CRM has an MCP server, register it in this project's `.gemini/settings.json` and list only its read tools under `includeTools`, so the review cannot change a record. No MCP server? An export added with `@deals.csv` works the same way. Sign-in tokens for MCP servers are stored in `~/.gemini/mcp-oauth-tokens.json`, outside the project, so they do not end up in the folder you share. Either way, keep raw records in a folder the drafts never quote from, and let only anonymized briefs reach `drafts/`. Running the analysis under `--approval-mode=plan` adds one more guard: nothing gets written until you have read the plan.
**Why this matters:** This connects marketing with the questions salespeople repeatedly need to answer. It also helps you avoid writing persuasive content about problems your buyers do not consider important.
## 10. Prepare Relevant Conversation Briefs
When someone responds to a post, the best next step depends on what they said and whether a business conversation would be welcome. Engagement alone does not show real business interest.
> Review these LinkedIn conversations I have supplied: [comments, inbound messages, or manually recorded interactions].
> Group them into:
> Questions that deserve a useful public answer.
> Conversations where sharing a resource would help.
> Explicit interest in our offer.
> General discussion with no commercial next step.
> For each relevant conversation, summarize the person's stated need, available business context, and what remains unknown.
> Draft a response that addresses their actual message before introducing anything else. Where appropriate, suggest one follow-up question or a resource we already have.
> Do not infer business interest from a like, invent familiarity, or force a meeting request into a conversation that does not support one. Keep all replies as drafts for me to review and send.
**In Gemini CLI:** paste the comments and messages into `inbox/` and add the file with `@`. Gemini CLI has no LinkedIn access, so the replies can only land as drafts in `replies/`, which is what this prompt asks for. Have each reply written directly under the comment it answers, so checking tone and facts takes one read. For public replies where you want a few more options to edit, the [LinkedIn comment generator](/tools/linkedin/comment-generator) gives you variants to start from. When a reply is ready, `/copy` puts the last response on your clipboard, ready to paste into LinkedIn yourself.
**Why this matters:** Preparation can make your responses more thoughtful without turning every interaction into a sales sequence. Sometimes the right outcome is simply a useful answer.
## 11. Report on Business Results With Clear Attribution
Impressions help you understand distribution, but they cannot tell you whether the right people became interested or whether a post contributed to a deal.
> Combine my supplied LinkedIn analytics, tracked website visits, inbound inquiry records, and relevant CRM data for [period].
> Report on:
> Reach and engagement by post, topic, and format.
> Qualified inbound conversations.
> Resource sign-ups and demo requests where tracking exists.
> Opportunities with documented LinkedIn touchpoints.
> Content production time and review effort.
> Separate directly tracked conversions, self-reported discovery, and possible influence. Do not attribute an entire deal to LinkedIn because one contact engaged with a post.
> Highlight posts that attracted relevant buyers, posts that reached a broad but less relevant audience, and posts with insufficient data to judge.
> Finish with three findings, three limitations, and one recommended experiment. If possible, assess posts at consistent ages so newly published content is not unfairly compared with older posts.
**In Gemini CLI:** if the exports live in several places, `gemini --include-directories ../analytics,../crm-exports` lets one session read them all. This report is also the natural candidate for headless mode: `gemini -p "..." --output-format json` returns structured output a small script can save as `reports/2026-11.json`, which makes month-to-month comparisons easy. Use `stream-json` instead when you want to watch a long run event by event. If your exports already land in a GitHub repository, the official Gemini CLI GitHub Action can run the same prompt inside a workflow there. Sanity-check reach on individual posts with the [LinkedIn impressions calculator](/tools/linkedin/impressions-calculator).
**Why this matters:** Better reporting gives you a reason to repeat or change an approach. It also makes uncertainty visible instead of turning incomplete tracking into a confident revenue claim.
## 12. Turn Feedback Into a Better System
Every edited draft contains information about your standards. Capture the recurring lessons so you spend less time correcting familiar problems.
> Compare the original drafts, my edits, final published versions, and available performance data from [period].
> Identify:
> Voice corrections I have made repeatedly.
> Claims that needed more evidence.
> Ideas that became clearer after a change in framing.
> Formatting changes that improved readability.
> Topics that generated useful buyer conversations.
> Propose updates to the voice guide, research briefs, and editorial checklist. For every proposed rule, show an example, explain its purpose, and note when an exception may be appropriate.
> Keep stylistic preferences separate from performance hypotheses. Do not create a permanent rule from one successful or unsuccessful post.
> Return a short change log for my approval and suggest one controlled experiment for the next month.
**In Gemini CLI:** keep drafts and published versions in git and let the agent run `git diff` through its shell tool, so it compares what you actually changed rather than what it remembers. With checkpointing on, every edit it then makes to the voice guide can be undone with `/restore`, so trying a proposed rule costs nothing. Approved rules go into `context/voice-guide.md` and the command files in `.gemini/commands/`, followed by `/memory refresh`. Save `/memory add` for one-line facts, rules you want to review later belong in files. Once the system works, an extension can package your commands, context files and MCP settings together, so a teammate installs the whole setup with one `gemini extensions install`.
**Why this matters:** This is how the workflow becomes easier to manage over time. Your corrections become usable guidance, while performance ideas remain testable rather than hardening into superstition.
## How to Use All 12 Prompts
Build the workflow in stages so you can inspect the output before adding another recurring job.
Week 1: Establish the foundation. Load your business context, run prompt 1, and check the voice guide against writing you would actually publish.
Week 2: Build your research backlog. Run prompts 2-4 using a manageable set of customer conversations, market sources, and supplied LinkedIn examples.
Week 3: Produce the first batch. Use prompts 5-7 to turn approved material into a calendar and a small number of drafts.
Week 4: Strengthen the review process. Run prompt 8, publish the posts you approve, work the first hour on each one, and record the changes you make.
Weeks 5-6: Connect content with conversations. Add prompts 9 and 10 where you have enough sales context and inbound activity to make them useful.
Then repeat monthly: Use prompts 11 and 12 to review results, improve the instructions, and choose the next experiment.
For any recurring job, define its inputs, destination, frequency, and owner. Test a run before relying on the schedule, and have Gemini CLI report missing access or incomplete work.
Gemini CLI has no scheduler of its own, recurring runs come from outside. Headless mode (`gemini -p` with `--output-format json` or `stream-json`) is built for scripts, so a cron entry or a CI workflow can run the monthly report from prompt 11, and the official GitHub Action covers repository-based setups. Keep each recurring prompt in a file or a custom command, so the scheduled run and the one you start by hand use identical instructions. Skip `--yolo`, which approves every tool call automatically, unless the run happens inside a sandbox.
A monthly cron entry can be as plain as this, with the prompt text kept in a file so you can edit it without touching the schedule:
```
0 8 1 * * cd ~/linkedin && gemini -p "Run the monthly report prompt in prompts/11-report.md on the files in reports/data/" --output-format json > reports/latest.json
```
Run the same command by hand first. If the output says a file was missing or a source could not be read, fix that before the schedule takes over.
Publishing stays manual on purpose. To keep the calendar from prompt 6 on track, our [free social media scheduler](/tools/free-tools/free-social-media-scheduler) sends an email or Telegram reminder when each post is due, you open LinkedIn and post it yourself.
You do not need 12 separate agents on day one.
Start with the job that consumes the most time and produces an output you can reliably evaluate.
## The Real Talk
Gemini CLI can help you organize research, retrieve useful evidence, prepare drafts, and learn from your edits. Because it all lives in files and commands, the system is easy to inspect and rerun. The quality still depends on the experience and judgment you bring into the system.
That means having a real opinion, being willing to explain it, and noticing when a polished draft says something you would never defend in a conversation.
When a post from this system goes live and you want its golden hour covered, start free on aaas.market.
Otherwise, load your context and run prompt 1. Improving the inputs will make every step after it more useful.