AI SEO Content Brief Generator Agent Template

The SEO Strategist Agent turns one topic line into a sourced content brief, real keywords, a dated SERP snapshot, and a competitor-page teardown, using required DataForSEO data, pausing at checkpoints for your approval. This template acts as a starting point: open the agent and use Use AI to help draft or update its instructions. Adding new agents or connecting new tools is done manually in the canvas.

• What it does: Turns one topic line into a fully sourced SEO content brief, primary and secondary keywords with real metrics, a dated SERP snapshot, competitor-page teardown, outline, FAQ, and meta title/description.
• Best for: Content marketers, SEO writers, and agencies who need a sourced brief before assigning or drafting an article.
• Apps used: DataForSEO (required), AWS AgentCore Code Interpreter (required), Web Search (optional).
• Setup time: About 15 to 20 minutes, including connecting DataForSEO, wiring the Code Interpreter, and a one-time onboarding interview.

Last verified from workflow config August, 2026. Includes common failure modes and fixes.

Problem this solves

• Briefs get written from gut feel. A writer or marketer picks a topic, skims a few competitor pages, and guesses at subtopics, there's no real record of what's already ranking, what a competitor page actually covers, or what people are asking around the topic.
• "SEO audit" tools score your site, not your next article. Most tools in this space run a technical crawl (page speed, broken links, Core Web Vitals) and hand you a health score. That's a different job from deciding what to write next and proving the decision with evidence.
• Trust in AI-written research is thin. Reddit's own SEO community is actively asking whether ChatGPT or Claude can just write the brief now, and the honest answer is that an LLM without real search data will happily invent volume numbers and difficulty scores that look right and aren't.
• Standardizing research across writers or clients is hard. Without a repeatable process, every brief looks different, has different evidence quality, and takes a different amount of time depending on who wrote it.

How do you build an SEO content brief generator yourself?

The general shape of this category is the same everywhere: a keyword-data API (search volume, difficulty, related terms), a SERP-fetching step (what's actually ranking today), a competitor-page parsing step (what the top results actually cover), and an LLM that assembles the brief from all three. Some setups add a backlink or domain-authority check to weigh how hard a keyword really is to rank for.

Building this yourself with Claude Code, Codex, or a custom script is a real option, not a fallback. You'd need your own DataForSEO or equivalent SERP API key, a parser for the raw API responses (a single keyword or SERP call can return thousands of lines of JSON), and your own checkpoint logic so a human reviews the keyword cluster before the agent writes 2,000 words based on it. None of that is exotic engineering, it's a week or two of integration and testing work, plus ongoing maintenance whenever an API response shape changes.

Cloning this template skips that integration work. The DataForSEO connection, the response parser (dfs_parse.py running inside the Code Interpreter tool, the same tool used to build charts and reports in the Data Analysis and Visualization template), the four-checkpoint approval flow, and the source-tagging rule are already built and tested, you connect your own DataForSEO account and go through a short onboarding interview instead of writing the pipeline from scratch.

Setup guide

Clone the template into your workspace. It's a single-agent Workforce template, one agent node, a plain text chat trigger, no multi-agent handoff to configure.

*All attached skills load and install automatically on clone, give it a few seconds after cloning before you open the agent so they finish attaching.

Step 1: Connect DataForSEO and wire the Code Interpreter

Open the agent canvas and connect your own DataForSEO login and password to the DataForSEO tool node, it ships disconnected and is pay-as-you-go, not a bundled credit.

Then confirm the AWS AgentCore Code Interpreter tool is wired to the agent. Without it, the agent drops into a lean mode with a lower research limit and no automated parsing.

Step 2: Run the onboarding interview to save your SEO profile

Send the agent setup (or just start a conversation with nothing saved yet, it triggers automatically). It runs a three-turn interview, business and site domain, primary market and language, audience, then three to five competitor domains, money pages, and brand or never-target terms, then your keyword-difficulty comfort band, volume floor, and call-budget preference.

After you approve, it runs a small enrichment pass on your own domain and proposes three to five starter topics based on real data, no extra calls needed.

Customization knobs: keyword-difficulty band (default 0-55), volume floor (default 50), call-budget override (default 25 per run), a fully unattended flag that turns the first three checkpoints into FYI notes, and a locale override like | market: Germany / de.

Step 3: Test with one in-scope prompt and one edge-case prompt

Send a real topic line, for example ai email deliverability | goal: leads | new page, and walk through the four checkpoints (Scope verdict, Cluster approval, Evidence digest, Brief approval) to see the full pipeline. Then test an edge case, send growth opportunities to see the discovery scan, or interrupt a brief mid-run and send continue to confirm it resumes from the last completed step instead of starting over.

Step 4: Deploy and run your first real brief

There's one trigger to name, the agent starts from a plain chat message, so deployment is simply making sure the right team members can message the agent directly (no secondary channel to configure for this template). Run your first real topic line once setup is verified.

Common issues

• DataForSEO not connected yet. The agent checks for both DataForSEO and the Code Interpreter at the start of every conversation and says plainly that it can't proceed without them, it will not guess at metrics to keep going.
• Code Interpreter missing. The agent falls back to lean mode, a mining limit of 30 and no dfs_parse.py parsing, which means slower runs and no CSV export.
• Wrong locale saved. The agent's own instructions call an incorrect location_name or language_code "silent garbage data," double-check the market and language you set during onboarding before running a real brief.
• Sending an unclear approval. The QA step hard-gates on an explicit approval message before marking a brief delivered, a vague "looks fine" won't move it past the final checkpoint.

Who it's for

• In-house content marketer or SEO lead at a small-to-mid B2B or SaaS team who owns content output and needs to know what a competitor already covers before assigning a topic. The brief includes a dated SERP snapshot and a competitor-page teardown, not a generic outline.
• Freelance SEO consultant or small agency managing multiple client sites who wants one standardized brief process instead of re-explaining context for every account. Onboarding captures competitor domains, money pages, and never-target terms per profile, so the same agent runs consistently across clients.
• Freelance or in-house SEO content writer who wants a sourced brief instead of guessing at subtopics. The FAQ list is pulled from real long-tail and People-Also-Ask-style questions, and every number in the brief is tagged by source, an unlabeled number is treated as a defect, not a shortcut.
• Growth or marketing lead at a startup asking what to write next. Opportunities mode is a separate, capped scan that returns Quick Wins (positions 8-30), Gaps versus a competitor, and Pillar bets as a ranked list plus an opportunities.csv file, a planning pass, not just a single brief.
• Teams already drafting with ChatGPT or Claude who need the strategy layer upstream of drafting. This agent produces the sourced brief, it does not write the final article, which is the honest answer to the Reddit question of whether AI already replaces brief-writing.

No DataForSEO connected yet? The agent states plainly that it can't proceed and stops rather than guessing at any metric. No SEO profile saved yet? The first message on a fresh setup always triggers the onboarding interview automatically, you can't skip straight to a brief without defining your domain, market, and competitors first.

What the agent does

• Runs a three-turn onboarding interview and saves a reusable SEO profile (domain, market, competitors, money pages, difficulty band).
• Scans your own ranked keywords for quick-win update candidates already sitting in positions 8 through 30.
• Runs a capped competitor domain-gap scan to surface keywords a competitor ranks for that you don't.
• Pulls a live, dated SERP snapshot for your target keyword and tears down what the top-ranking competitor pages actually cover.
• Assembles a sourced content brief, primary and secondary keywords with real metrics, an outline, an FAQ list sourced from real questions, an exact-character-counted meta title and description, and an internal-link plan.
• Tags every number by source (a real API call, your profile, a calculation, or a flagged gap) instead of inventing plausible-looking figures.
• Pauses at four checkpoints (scope, cluster, evidence, brief approval) so you can redirect before the agent commits more of its call budget.
• Resumes an interrupted run when you send continue, instead of restarting the whole pipeline.
• Exports keywords.csv and opportunities.csv alongside the finished brief file.
• Keeps an archive copy of each delivered brief for future duplicate-topic checks.

How it works

1. You send a topic line or a flag. A real topic (ai email deliverability | goal: leads | new page), setup, or growth opportunities.
2. The agent loads or builds your SEO profile. If none is saved, onboarding runs first, no pipeline step starts on an empty profile.
3. Scope and keyword-universe pass. The agent scopes the request and builds the keyword cluster, then stops at a Scope verdict checkpoint (GO, GO-WITH-FLAG, or NO-GO) for you to confirm.
4. Live SERP snapshot and competitor teardown. It pulls a dated SERP for the approved cluster and tears down what's actually ranking, then stops at an Evidence digest checkpoint.
5. Brief assembly. Outline, FAQ, meta title and description, and internal-link plan get assembled from the approved evidence, then the full brief stops at a Brief approval checkpoint, led by an update-versus-new verdict.
6. QA and delivery. Once you send an explicit approval, the agent runs its QA step and delivers content_brief_FINAL.md plus keywords.csv, with an archive copy saved for future duplicate-topic checks.

Requirements

DataForSEO is required, not optional. This template does not run without it, connecting it is a self-service, pay-as-you-go step (your own API login and password), not a bundled credit or an add-on you can skip.

• DataForSEO API login and password, connected on the DataForSEO tool node.
• AWS AgentCore Code Interpreter, wired to the agent, it runs the response parser and produces the CSV exports.
• Web Search (optional, already enabled), used only for fact-currency checks and to harvest real question phrasing when a SERP endpoint doesn't return People-Also-Ask results, capped at five searches per run.
• SEO profile inputs, gathered through the onboarding interview: business name and what it sells, site domain, primary market and language, audience, three to five competitor domains, money pages, brand or never-target terms, keyword-difficulty band, volume floor, and call-budget preference.

Beyond these three tools, this agent doesn't connect to any other third-party app by default. If you want to route the finished brief somewhere else, SketricGen's library of 2,000+ apps covers optional add-ons like sending it to a CRM or a docs tool once you're ready.

Apps used

No other third-party connector is wired by default. See SketricGen's 2,000+ app library if you want to add a delivery step later.

Use cases

Brief a new blog post before you assign it Send one topic line and get a sourced brief back before you hand it to a writer. Best for in-house content marketers who own the assignment step.

Run the same standardized brief process across client accounts One onboarding profile per client keeps competitor domains, money pages, and never-target terms consistent across every brief you produce. Best for freelance consultants and small agencies.

Get a sourced brief instead of guessing at subtopics Every subtopic and FAQ question in the brief traces back to a real SERP or People-Also-Ask signal. Best for SEO content writers who want evidence, not a generic outline.

Find your next 5 content topics from real ranking and gap data Opportunities mode returns Quick Wins, competitor Gaps, and Pillar bets as a ranked list plus a CSV export. Best for growth and marketing leads planning a content calendar.

Feed a sourced strategy brief into your existing AI writing step This agent stops at the brief, it doesn't draft the article, so it slots cleanly upstream of whatever AI drafting tool your team already uses. Best for teams already writing with ChatGPT or Claude who need the research layer.

Example outputs

Example: brief pipeline input and output Input: ai email deliverability | goal: leads | new page Output: content_brief_FINAL.md, primary and secondary keywords with real search-volume and difficulty numbers, a dated SERP snapshot, a competitor-page teardown, a section-by-section outline, an FAQ list sourced from real long-tail questions, an exact-character-counted meta title and description, and an internal-link plan, plus a companion keywords.csv.

Example: opportunities scan input and output Input: growth opportunities Output: a ranked list of Quick Wins (your own keywords already in positions 8-30), Gaps versus a saved competitor, and Pillar bets, plus an opportunities.csv file of ready-to-send brief requests.

Why you need this template

• Time saved. One topic-line message replaces a manual multi-tab research session across a keyword tool, a SERP checker, and however many competitor tabs you'd normally open.
• Evidence you can actually trust. Every number is tagged by source, a real API call, your saved profile, a calculation, or a flagged gap, so nothing in the brief is a plausible-sounding guess.
• Consistency across writers and clients. The same checkpointed process runs every time, so brief quality doesn't depend on who happened to write it that week.
• Traceability when a brief gets questioned. An archive copy of every delivered brief is kept for future duplicate-topic checks, so you can see exactly what was researched and when.