How to Use Frase for Table Of Contents Generation in 2026

Originally published at https://seointent.com/blog/frase-for-table-of-contents-generation

TL;DR

- Frase for table of contents generation works best when you pair its SERP-analysis brief with a targeted outline prompt — you get a TOC that reflects what's actually ranking, not just what the AI guesses.

- The five-step workflow below takes under 20 minutes and produces a publish-ready TOC structure aligned to search intent.

- Frase edges out general-purpose tools like ChatGPT for this task because it pulls live competitor data before generating — context that generic models simply don't have.

- If you're doing this at scale across dozens of pages, SEOintent automates the whole process without you hand-crafting a single prompt.

Frase for table of contents generation is the practice of using Frase's AI writing and SERP-research environment to automatically draft a hierarchical heading structure for a piece of content — pulling from live competitor outlines, keyword clustering, and on-page NLP signals to produce a TOC that matches real search intent rather than a generic template.

People are searching this right now because content teams are drowning. AI writing tools are everywhere, but most produce TOCs that feel copy-pasted from Wikipedia. Surfer SEO gets the on-page optimization angle right but its outline builder is rigid. Clearscope is strong on NLP scoring but weak on TOC automation. Neither fully answers "how do I go from keyword to structured outline in one place?" That's the gap this article fills. If you're also building content at volume, check out our programmatic SEO guide for the broader strategy behind scaling this workflow.

What is Frase For Table Of Contents Generation?

Frase For Table Of Contents Generation is a workflow inside the Frase SEO tool where you combine its research brief — populated with SERP competitor headings — and its AI assistant to produce a structured H2/H3 outline you can use directly as your article's table of contents. It matters because structure is the single biggest lever for topical authority.

When you use Frase for automated table of contents generation, you're not just asking an AI to brainstorm headings. You're feeding it actual competitor heading data pulled from the top 20 search results, which means the TOC reflects what Google's NLP systems already reward. According to Google's official SEO guide, clear page structure signals are a core factor in how Googlebot understands content — making a well-built TOC far more than a UX nicety.

Why Use Frase for Table Of Contents Generation Specifically?

Frase earns its place in this workflow because it collapses the research and generation steps into a single interface. Most tools make you pull competitor headings manually, then paste them into a separate AI tool, then re-format. Frase skips that entirely — its brief auto-populates with real SERP data, and its AI assistant reads that context before it writes. That combination saves time and produces outlines that are grounded in what already ranks.

- SERP-grounded context — Frase scrapes the top 20 competitors for your keyword and surfaces their exact headings, so your TOC prompt has real signal to work from rather than thin AI guesses. This is the core advantage over using AI for table of contents generation in isolation.

- Built-in keyword clustering — The tool groups related subtopics from competitor pages, which makes it straightforward to spot H3-level gaps your rivals are missing. For agencies running multiple clients, this pairs directly with our AI SEO for agencies workflow.

- Iterative prompt environment — Frase's assistant panel sits next to the brief, so you can refine your table of contents generation prompt and re-run it without switching tabs or losing context.

- Topic score feedback — After generating your TOC, Frase scores it against competitor coverage immediately, so you know before writing whether you're missing critical subtopics.

How to Use Frase for Table Of Contents Generation: A 5-Step Workflow

The whole workflow runs inside a single Frase document. You need your target keyword, roughly 15 minutes, and a clear sense of your audience's intent. Steps 1 through 3 are research — steps 4 and 5 are generation and refinement. Most people get tripped up at step 4 because they use a prompt that's too vague and Frase defaults to generic headings.

- Step 1: Create a new Frase document and run the SERP brief. Open Frase, hit "New Document," and enter your target keyword. Frase will pull the top 20 results and populate the research panel with competitor headings, word counts, and topic clusters. Let it finish loading — don't skip ahead. The brief is the foundation everything else builds on.

- Step 2: Filter competitor headings by relevance. In the research panel, scan the competitor headings and manually star or hide the ones that are clearly off-topic for your specific angle. This takes about three minutes but dramatically improves what the AI generates. Think of it as curating your table of contents generation prompt's source material before you write a single word of instruction.
  Frase AI Prompt: "Based on the competitor headings in this brief, generate a complete H2/H3 table of contents for a 2,000-word article targeting '[your keyword]'. Prioritize headings that appear in 3+ competitor pages. Group related subtopics under shared H2s. Avoid redundant sections."

- Step 3: Run the generation prompt and review raw output. Paste the prompt above into Frase's AI assistant, run it, and read the output critically — don't just accept it. Cross-reference against ChatGPT (OpenAI) if you want a second opinion on heading phrasing, since sometimes a fresh model catches framing angles Frase's context misses. The goal here is a rough TOC skeleton, not a finished product.

- Step 4: Restructure for search intent alignment. Take the raw TOC and reorder sections so the highest-intent content comes first. If someone's searching "how to use frase for SEO," they want the workflow before the background theory — flip any definition-heavy sections toward the bottom unless they're answering a clear definitional query.
  Frase AI Prompt: "Reorder the following table of contents so that actionable steps appear before explanatory context. Keep all H2s and H3s intact. Output as a clean numbered outline: [paste your current TOC here]"

- Step 5: Validate the TOC against your topic score and publish the structure. With your restructured TOC in place, check your Frase topic score. Aim for 40+ before you start writing. If sections are missing coverage, add H3s for the flagged topics now — it's much easier to adjust structure before the article exists than after. For schema-level TOC markup, run your finished outline through our free schema markup generator to get structured data ready for Google.




**Pro tip:** Run your TOC prompt twice — once with Frase's default temperature and once after manually removing all competitor headings that appear in fewer than two sources. The second run produces tighter, less noisy outlines because you've stripped low-consensus headings from the context pool.


**Further reading:** If this workflow is part of a larger content operation, you'll want to go deeper on the infrastructure behind it. Explore our [AI SEO services](https://seointent.com/ai-seo-services) for done-for-you implementation, check the [agency partner program](https://seointent.com/agency-program) if you're running client sites at volume, and compare tool costs on our [compare plans](https://seointent.com/pricing) page before committing to a stack.

What Frase's Output Actually Looks Like

Here's a realistic example of what you'd get running the step 2 prompt above on a keyword like "how to write a product comparison article." This was produced using Frase's standard AI assistant with a brief populated from 15 SERP competitors — not cherry-picked, not rewritten. Expect this level of specificity on a well-searched keyword. You'll usually need one round of H3 consolidation before it's ready to use.

H2: What is a Product Comparison Article?

H3: Definition and Search Intent

H3: When to Use This Format Over a Standard Review

H2: How to Structure a Product Comparison Article

H3: Choosing the Right Products to Compare

H3: Deciding on Comparison Criteria

H3: Table vs. Narrative Format — Which Converts Better

H2: Writing the Introduction Without Losing the Reader

H3: The Hook Formula That Works for Comparison Queries

H2: On-Page SEO for Product Comparisons

H3: How to Use Schema Markup for Comparison Pages

H3: Internal Linking Strategy for Comparison Content

H2: Common Mistakes in Product Comparison Articles

H3: Being Too Balanced (And Why It Kills Conversions)

H2: Frequently Asked Questions

H3: How Long Should a Comparison Article Be?

H3: Should I Include Affiliate Links?

The structure is solid — it covers intent, execution, SEO, and mistakes, which is exactly what a SERP-grounded TOC should do. The weakness is that the H3s under "On-Page SEO" are thin and generic; I'd replace the schema H3 with something more specific to the comparison format. The FAQ section at the bottom is predictable — consider moving one FAQ H3 higher if it answers a primary searcher question.

Frase vs Other AI Tools for Table Of Contents Generation

The three main competitors worth comparing are Anthropic's Claude, Surfer SEO, and Jasper AI. Claude produces the most linguistically varied headings but has no SERP context unless you paste it in manually. Surfer's outline builder is SERP-grounded but feels mechanical and doesn't iterate well. Jasper is strong for brand voice but genuinely weak at technical SEO structure. Frase wins for content teams who want speed plus SERP grounding in one place, but if you're a developer who wants full prompt control, Claude with the Claude API docs gives you more flexibility.

  ToolBest forWeaknessFree tier?


  **Frase**SERP-grounded automated table of contents generation with one-click brief populationRepetitive H3s on niche keywords with few SERP competitorsLimited — 1 document trial only
  Anthropic's ClaudeCreative, varied heading phrasing; excellent for long-form structuresNo live SERP data; manual context injection requiredYes — Claude.ai free tier available
  Surfer SEONLP-scored outlines with direct correlation to top-ranking pagesOutline builder is rigid; hard to iterate on structureNo — paid plans only
  Jasper AIBrand-voice consistency across heading setsWeak on technical SEO structure; TOCs feel marketing-first7-day trial only

Frase is the right default pick for content marketers who want using AI for table of contents generation to be fast and grounded in real data. If you're already paying for Surfer and want a Frase alternative, the gap in TOC quality is smaller than Frase's marketing suggests — test both on the same keyword before committing.

Pro tip: If Frase's TOC feels too derivative of competitor structures, paste it into the OpenAI's official docs API playground and prompt GPT-4 to "rewrite these headings as if the author has a strong contrarian point of view" — you'll get differentiated angles while keeping the underlying structure intact.

3 Mistakes People Make With Frase For Table Of Contents Generation

Most mistakes with this workflow come from treating Frase like a one-click solution rather than a research-assisted environment. People either skip the brief entirely, over-trust the raw output, or ignore the topic score after generation. The common thread is impatience — the tool rewards the 10 minutes of setup it asks for. Here's what to avoid — and what to do instead:

- Mistake 1: Running the prompt before the brief loads fully. If you paste in your keyword and immediately fire the AI prompt, Frase hasn't finished pulling SERP data — so the assistant generates from thin context. Wait for the topic score and competitor headings to populate first. This single fix improves output quality more than any prompt tweak.


Mistake 2: Accepting the first TOC output without checking the topic score. A Frase topic score below 35 on your generated outline means you're missing significant competitor coverage. Use the meta tag analyzer to cross-check whether missing topics are actually searcher priorities, then add H3s for the gaps before writing begins.
Mistake 3: Using the same generic prompt every time. A vague prompt like "write a table of contents for this topic" ignores all the research context Frase built. Tailor your table of contents generation prompt to include word count, audience sophistication level, and the specific angle of your piece — you'll get a TOC that actually fits the article rather than a universal template. If you want a true alternative to Jasper AI or a Copy.ai alternative for this kind of structured output, the prompt specificity is what separates good tools from great results.

Automate Table Of Contents Generation With SEOintent

If you're running this process across 50 or 500 pages, hand-crafting Frase prompts doesn't scale. SEOintent automates the entire TOC generation pipeline with two core features: its Bulk Outline Builder, which pulls SERP data and generates structured H2/H3 outlines for entire keyword lists in one batch, and its Intent Clustering engine, which groups keywords by searcher intent before generating outlines — so you're not producing duplicate structures for closely related queries. It's a direct upgrade from manual Frase workflows for teams that have moved past one-at-a-time content production. Check out the full capability set at see what SEOintent does, and if you're comparing it against your current Frase setup, the feature gap for high-volume TOC work is significant.

Frequently Asked Questions About Frase For Table Of Contents Generation

Can Frase generate a table of contents automatically without a manual prompt?

Frase doesn't produce a full TOC with zero input — you still need to trigger the AI assistant with a prompt. But its "Generate Outline" feature in the editor does produce a basic H2 structure with a single click once your brief is loaded. It's less customizable than a manual prompt but good enough for a starting scaffold you then refine.

Is Frase better than ChatGPT for table of contents generation?

For most content marketers, yes — specifically because Frase has live SERP data baked in. ChatGPT (without plugins or browsing) is generating headings from training data, not from what's actually ranking today. That said, if you need highly creative or contrarian heading structures, ChatGPT's language flexibility often beats Frase's more conservative outputs. The best workflow combines both: use Frase for structure, ChatGPT for phrasing polish.

What's the best table of contents generation prompt to use in Frase?

The most reliable prompt structure is: specify your target keyword, your desired word count, your audience, and instruct Frase to prioritize headings that appear in three or more competitor pages. Explicitly ask for H2s and H3s with a ratio of roughly 1:2. Avoid open-ended prompts — the more constraints you give, the more useful the output. Revisit and tweak your prompt after seeing your topic score.

How does Frase compare to Surfer SEO for outline generation?

Surfer's outline tool is more tightly tied to its NLP scoring system, which means every heading is weighted against keyword frequency targets. Frase's approach is looser but more readable — the TOCs feel more like articles and less like keyword matrices. For pure search intent alignment, Surfer edges ahead. For speed and usability in a content team workflow, Frase wins. If you're evaluating both, run the same keyword through each and compare the H3 depth — that's where the real difference shows.

Does Frase support H3 generation inside table of contents, or just H2s?

Yes — Frase generates both H2 and H3 levels when you specify it in your prompt. Without explicit instruction, it tends to default toward H2-heavy outlines with shallow nesting. Always include a line in your prompt like "include H3 subheadings under each H2 to cover subtopics" to get the full hierarchical structure. The H3 quality depends heavily on how populated your SERP brief is, so keyword research quality directly affects TOC depth.

Is there an agency workflow for using Frase for table of contents generation at scale?

Frase does offer team seats and client workspace features, but it doesn't natively batch-generate TOCs across a keyword list. Agencies typically build a standardized Frase prompt template, assign one team member per content brief, and QA against the topic score threshold. For true scale — hundreds of pages per month — you'll want to look at dedicated infrastructure like our agency partner program, which is built specifically for this volume of structured content production.

What word count should I target when generating a TOC in Frase?

Set your target word count in the prompt to match the median word count of the top 5 competitors in your Frase brief — not the average, which gets skewed by outlier long-form pieces. For most informational keywords, that's between 1,400 and 2,200 words. The TOC structure should reflect that scope: a 1,500-word article needs 4-5 H2s maximum, while a 2,500-word piece can carry 6-7 comfortably without feeling padded.

More AI SEO Workflows

• How to Use Frase for Keyword Research in 2026
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• How to Use Frase for Competitor Keyword Analysis in 2026
• How to Use Frase for Long-Tail Keyword Discovery in 2026
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