Vibecode Surfer SEO
track this build5 steps, step by step0%A SERP-scrape-to-content-brief tool is buildable, but reliable SERP data, NLP scoring, editor workflow, AI articles, audits, and integrations create ongoing work.
You are building a lean indie version of Surfer SEO. Create the following project files first, then implement the application by following them. Keep the files updated as decisions change. Do not collapse this into a single README or prompt. ===== README.md ===== # Surfer SEO indie build ## Goal Build the smallest trustworthy replacement for the core Surfer SEO workflow for one developer or a tiny team. ## Scope Fetch top SERP pages via API, extract headings/entities/terms, score a draft, and produce brief/editor suggestions. ## Quick start 1. Install the documented dependencies. 2. Copy `.env.example` to `.env`. 3. Run the development command chosen during implementation. 4. Complete the acceptance checks in `BUILD_PLAN.md`. ## Honest limits This build deliberately does not replace: - SERP data reliability - scoring model - editor UX - AI article workflows - integrations - audits - support If those capabilities are essential, use Surfer SEO instead of pretending the gap is solved. ===== AGENTS.md ===== # Agent instructions - Optimize for a working, understandable weekend build. - Prefer the fewest moving parts that satisfy the brief. - Do not invent cryptography, security guarantees, APIs, or compliance claims. - Keep secrets out of source control and logs. - Add focused tests for destructive, security-sensitive, and data-loss paths. - Run the project checks before declaring the build complete. - Record any deliberate shortcut in the README under "Tradeoffs". ===== BUILD_PLAN.md ===== # Build plan ## Original build brief Build me a content-brief and draft-scoring tool to replace Surfer SEO, personal scale. Requirements: - A Node CLI with two commands: brief "<keyword>" and score <draft.md> "<keyword>". - brief: fetch the top 10 results from Serper.dev (key in .env), download each page, extract title, headings, and body text with cheerio + @mozilla/readability. - Compute across the winners: median word count, recurring H2/H3 topics, and the 30 most frequent meaningful terms via simple tf-idf. No NLP service. - Send that to an LLM (key in .env) to write briefs/<keyword>-YYYY-MM-DD.md: suggested outline, target word count, terms to cover, questions to answer. - score: compare my draft against the brief's term list and outline, print a coverage percentage and a table of missing terms in the terminal. - Cache every SERP response and fetched page in SQLite (better-sqlite3) so re-runs cost zero API credits. - No accounts, no telemetry, everything local except the Serper and LLM calls. - Out of scope: a writing editor with live scoring, site audits, and rank tracking. This outputs Markdown briefs, and page scraping will break on some sites · Serper is the one paid dependency, say both in the README. - README: where to get the Serper key and the rough API cost per brief. ## Required capabilities - search/SERP API - web scraper/parser - LLM API - content editor - scoring logic - hosted backend ## Delivery order 1. Scaffold the smallest runnable application and document its commands. 2. Implement the primary data model and core workflow. 3. Add validation, safe failure states, and persistence. 4. Cover the critical path with automated tests. 5. Exercise a clean install from the README and fix every missing step. ## Done when - A new user can go from clone to first successful workflow using only the README. - The core workflow works without paid infrastructure unless the brief requires it. - Tests cover the highest-risk behavior. - Known limitations are explicit rather than hidden. ===== .env.example ===== # Copy to .env and document every variable when it is introduced. # Never put real credentials in this file. APP_ENV=development # Add only values required by the selected implementation.
You are building a lean indie version of Surfer SEO. Create the following project files first, then implement the application by following them. Keep the files updated as decisions change. Do not collapse this into a single README or prompt. ===== README.md ===== # Surfer SEO indie build ## Goal Build the smallest trustworthy replacement for the core Surfer SEO workflow for one developer or a tiny team. ## Scope Fetch top SERP pages via API, extract headings/entities/terms, score a draft, and produce brief/editor suggestions. ## Quick start 1. Install the documented dependencies. 2. Copy `.env.example` to `.env`. 3. Run the development command chosen during implementation. 4. Complete the acceptance checks in `BUILD_PLAN.md`. ## Honest limits This build deliberately does not replace: - SERP data reliability - scoring model - editor UX - AI article workflows - integrations - audits - support If those capabilities are essential, use Surfer SEO instead of pretending the gap is solved. ===== AGENTS.md ===== # Agent instructions - Optimize for a working, understandable weekend build. - Prefer the fewest moving parts that satisfy the brief. - Do not invent cryptography, security guarantees, APIs, or compliance claims. - Keep secrets out of source control and logs. - Add focused tests for destructive, security-sensitive, and data-loss paths. - Run the project checks before declaring the build complete. - Record any deliberate shortcut in the README under "Tradeoffs". ===== BUILD_PLAN.md ===== # Build plan ## Original build brief Build me a content-brief and draft-scoring tool to replace Surfer SEO, personal scale. Requirements: - A Node CLI with two commands: brief "<keyword>" and score <draft.md> "<keyword>". - brief: fetch the top 10 results from Serper.dev (key in .env), download each page, extract title, headings, and body text with cheerio + @mozilla/readability. - Compute across the winners: median word count, recurring H2/H3 topics, and the 30 most frequent meaningful terms via simple tf-idf. No NLP service. - Send that to an LLM (key in .env) to write briefs/<keyword>-YYYY-MM-DD.md: suggested outline, target word count, terms to cover, questions to answer. - score: compare my draft against the brief's term list and outline, print a coverage percentage and a table of missing terms in the terminal. - Cache every SERP response and fetched page in SQLite (better-sqlite3) so re-runs cost zero API credits. - No accounts, no telemetry, everything local except the Serper and LLM calls. - Out of scope: a writing editor with live scoring, site audits, and rank tracking. This outputs Markdown briefs, and page scraping will break on some sites · Serper is the one paid dependency, say both in the README. - README: where to get the Serper key and the rough API cost per brief. ## Required capabilities - search/SERP API - web scraper/parser - LLM API - content editor - scoring logic - hosted backend ## Delivery order 1. Scaffold the smallest runnable application and document its commands. 2. Implement the primary data model and core workflow. 3. Add validation, safe failure states, and persistence. 4. Cover the critical path with automated tests. 5. Exercise a clean install from the README and fix every missing step. ## Done when - A new user can go from clone to first successful workflow using only the README. - The core workflow works without paid infrastructure unless the brief requires it. - Tests cover the highest-risk behavior. - Known limitations are explicit rather than hidden. ===== .env.example ===== # Copy to .env and document every variable when it is introduced. # Never put real credentials in this file. APP_ENV=development # Add only values required by the selected implementation.
You are building a production product version of Surfer SEO. Create the following project files first, then implement the application by following them. Keep the files updated as decisions change. Do not collapse this into a single README or prompt. ===== PRODUCT.md ===== # Surfer SEO product brief ## Problem A SERP-scrape-to-content-brief tool is buildable, but reliable SERP data, NLP scoring, editor workflow, AI articles, audits, and integrations create ongoing work. ## Product outcome Fetch top SERP pages via API, extract headings/entities/terms, score a draft, and produce brief/editor suggestions. ## Target user A serious builder who needs a maintainable product foundation rather than a one-off demo. ## Required capabilities - search/SERP API - web scraper/parser - LLM API - content editor - scoring logic - hosted backend ## Explicit non-goals for v1 - SERP data reliability - scoring model - editor UX - AI article workflows - integrations - audits - support ## Success criteria - The primary workflow is measurable end to end. - Setup is reproducible in a clean environment. - Failure, recovery, and support paths are documented. - Product claims match what the implementation actually guarantees. ===== ARCHITECTURE.md ===== # Architecture ## Starting brief Build me a content-brief and draft-scoring tool to replace Surfer SEO, personal scale. Requirements: - A Node CLI with two commands: brief "<keyword>" and score <draft.md> "<keyword>". - brief: fetch the top 10 results from Serper.dev (key in .env), download each page, extract title, headings, and body text with cheerio + @mozilla/readability. - Compute across the winners: median word count, recurring H2/H3 topics, and the 30 most frequent meaningful terms via simple tf-idf. No NLP service. - Send that to an LLM (key in .env) to write briefs/<keyword>-YYYY-MM-DD.md: suggested outline, target word count, terms to cover, questions to answer. - score: compare my draft against the brief's term list and outline, print a coverage percentage and a table of missing terms in the terminal. - Cache every SERP response and fetched page in SQLite (better-sqlite3) so re-runs cost zero API credits. - No accounts, no telemetry, everything local except the Serper and LLM calls. - Out of scope: a writing editor with live scoring, site audits, and rank tracking. This outputs Markdown briefs, and page scraping will break on some sites · Serper is the one paid dependency, say both in the README. - README: where to get the Serper key and the rough API cost per brief. ## Boundaries Separate the product into replaceable modules for interface, application logic, persistence, external integrations, and operational concerns. Keep domain logic independent from delivery frameworks and vendors. ## Production baseline - Configuration: validated at startup with safe local defaults where possible. - Security: least privilege, input validation, secret redaction, rate limits on abuse-prone paths, and no invented security primitives. - Data: explicit schema and migrations, transactional writes where integrity matters, backup and restore instructions. - Integrations: adapters around third-party providers, idempotent webhook or job processing, bounded retries, and timeouts. - Observability: structured logs with request or operation IDs, an error-tracking hook, and health/readiness checks where a server exists. - Quality: unit tests for domain rules, integration tests at module boundaries, and one end-to-end critical-path test. ## Decision records For each major dependency, document why it was chosen, its failure mode, and how it can be replaced. Do not introduce infrastructure until a requirement justifies it. ===== AGENTS.md ===== # Agent instructions - Read `PRODUCT.md` and `ARCHITECTURE.md` before changing code. - Implement milestone by milestone; keep each change reviewable and leave the application runnable. - Treat authentication, payments, encryption, imports, webhooks, and destructive actions as high-risk boundaries when present. - Never invent cryptography or silently weaken a requirement to make a test pass. - Use provider interfaces for external services and deterministic fakes in tests. - Add migrations and rollback or recovery notes for persistent data changes. - Log useful operational context without credentials, tokens, passwords, or personal data. - Update documentation and run all checks before completing a milestone. ===== MILESTONES.md ===== # Delivery milestones ## M0 — Decisions and scaffold - Confirm the runtime, persistence model, threat boundaries, and deployment target. - Create a reproducible local environment and continuous checks. ## M1 — Core workflow - Implement the smallest end-to-end product path with validation and tests. - Keep integrations behind interfaces. ## M2 — Trust layer - Add secure failure behavior, recovery paths, audit-relevant events, and data safeguards. - Test abuse cases and destructive operations. ## M3 — Operability - Add structured logs, error reporting hooks, health signals, backup/restore documentation, and deployment configuration. ## M4 — Release gate - Run a clean-install test, critical-path end-to-end test, dependency review, and documented rollback exercise. - Compare the shipped behavior with `PRODUCT.md` and publish remaining limitations. ===== OPERATIONS.md ===== # Operations ## Before release - Validate configuration and secrets at startup. - Define backup, restore, and rollback procedures and test them. - Document logs, error tracking, health signals, and alert ownership. - Set dependency update and vulnerability review expectations. ## Incident checklist 1. Contain the issue without destroying evidence or user data. 2. Record the timeline and affected scope. 3. Rotate exposed secrets and revoke compromised sessions or credentials. 4. Restore from a verified source when needed. 5. Document the root cause, remediation, and regression test. ## Launch constraint Do not market omitted Surfer SEO capabilities as implemented. The v1 non-goals in `PRODUCT.md` remain user-visible limitations until they are deliberately delivered.
# Surfer SEO indie build ## Goal Build the smallest trustworthy replacement for the core Surfer SEO workflow for one developer or a tiny team. ## Scope Fetch top SERP pages via API, extract headings/entities/terms, score a draft, and produce brief/editor suggestions. ## Quick start 1. Install the documented dependencies. 2. Copy `.env.example` to `.env`. 3. Run the development command chosen during implementation. 4. Complete the acceptance checks in `BUILD_PLAN.md`. ## Honest limits This build deliberately does not replace: - SERP data reliability - scoring model - editor UX - AI article workflows - integrations - audits - support If those capabilities are essential, use Surfer SEO instead of pretending the gap is solved.
# Agent instructions - Optimize for a working, understandable weekend build. - Prefer the fewest moving parts that satisfy the brief. - Do not invent cryptography, security guarantees, APIs, or compliance claims. - Keep secrets out of source control and logs. - Add focused tests for destructive, security-sensitive, and data-loss paths. - Run the project checks before declaring the build complete. - Record any deliberate shortcut in the README under "Tradeoffs".
# Build plan ## Original build brief Build me a content-brief and draft-scoring tool to replace Surfer SEO, personal scale. Requirements: - A Node CLI with two commands: brief "<keyword>" and score <draft.md> "<keyword>". - brief: fetch the top 10 results from Serper.dev (key in .env), download each page, extract title, headings, and body text with cheerio + @mozilla/readability. - Compute across the winners: median word count, recurring H2/H3 topics, and the 30 most frequent meaningful terms via simple tf-idf. No NLP service. - Send that to an LLM (key in .env) to write briefs/<keyword>-YYYY-MM-DD.md: suggested outline, target word count, terms to cover, questions to answer. - score: compare my draft against the brief's term list and outline, print a coverage percentage and a table of missing terms in the terminal. - Cache every SERP response and fetched page in SQLite (better-sqlite3) so re-runs cost zero API credits. - No accounts, no telemetry, everything local except the Serper and LLM calls. - Out of scope: a writing editor with live scoring, site audits, and rank tracking. This outputs Markdown briefs, and page scraping will break on some sites · Serper is the one paid dependency, say both in the README. - README: where to get the Serper key and the rough API cost per brief. ## Required capabilities - search/SERP API - web scraper/parser - LLM API - content editor - scoring logic - hosted backend ## Delivery order 1. Scaffold the smallest runnable application and document its commands. 2. Implement the primary data model and core workflow. 3. Add validation, safe failure states, and persistence. 4. Cover the critical path with automated tests. 5. Exercise a clean install from the README and fix every missing step. ## Done when - A new user can go from clone to first successful workflow using only the README. - The core workflow works without paid infrastructure unless the brief requires it. - Tests cover the highest-risk behavior. - Known limitations are explicit rather than hidden.
# Copy to .env and document every variable when it is introduced. # Never put real credentials in this file. APP_ENV=development # Add only values required by the selected implementation.
# Surfer SEO product brief ## Problem A SERP-scrape-to-content-brief tool is buildable, but reliable SERP data, NLP scoring, editor workflow, AI articles, audits, and integrations create ongoing work. ## Product outcome Fetch top SERP pages via API, extract headings/entities/terms, score a draft, and produce brief/editor suggestions. ## Target user A serious builder who needs a maintainable product foundation rather than a one-off demo. ## Required capabilities - search/SERP API - web scraper/parser - LLM API - content editor - scoring logic - hosted backend ## Explicit non-goals for v1 - SERP data reliability - scoring model - editor UX - AI article workflows - integrations - audits - support ## Success criteria - The primary workflow is measurable end to end. - Setup is reproducible in a clean environment. - Failure, recovery, and support paths are documented. - Product claims match what the implementation actually guarantees.
# Architecture ## Starting brief Build me a content-brief and draft-scoring tool to replace Surfer SEO, personal scale. Requirements: - A Node CLI with two commands: brief "<keyword>" and score <draft.md> "<keyword>". - brief: fetch the top 10 results from Serper.dev (key in .env), download each page, extract title, headings, and body text with cheerio + @mozilla/readability. - Compute across the winners: median word count, recurring H2/H3 topics, and the 30 most frequent meaningful terms via simple tf-idf. No NLP service. - Send that to an LLM (key in .env) to write briefs/<keyword>-YYYY-MM-DD.md: suggested outline, target word count, terms to cover, questions to answer. - score: compare my draft against the brief's term list and outline, print a coverage percentage and a table of missing terms in the terminal. - Cache every SERP response and fetched page in SQLite (better-sqlite3) so re-runs cost zero API credits. - No accounts, no telemetry, everything local except the Serper and LLM calls. - Out of scope: a writing editor with live scoring, site audits, and rank tracking. This outputs Markdown briefs, and page scraping will break on some sites · Serper is the one paid dependency, say both in the README. - README: where to get the Serper key and the rough API cost per brief. ## Boundaries Separate the product into replaceable modules for interface, application logic, persistence, external integrations, and operational concerns. Keep domain logic independent from delivery frameworks and vendors. ## Production baseline - Configuration: validated at startup with safe local defaults where possible. - Security: least privilege, input validation, secret redaction, rate limits on abuse-prone paths, and no invented security primitives. - Data: explicit schema and migrations, transactional writes where integrity matters, backup and restore instructions. - Integrations: adapters around third-party providers, idempotent webhook or job processing, bounded retries, and timeouts. - Observability: structured logs with request or operation IDs, an error-tracking hook, and health/readiness checks where a server exists. - Quality: unit tests for domain rules, integration tests at module boundaries, and one end-to-end critical-path test. ## Decision records For each major dependency, document why it was chosen, its failure mode, and how it can be replaced. Do not introduce infrastructure until a requirement justifies it.
# Agent instructions - Read `PRODUCT.md` and `ARCHITECTURE.md` before changing code. - Implement milestone by milestone; keep each change reviewable and leave the application runnable. - Treat authentication, payments, encryption, imports, webhooks, and destructive actions as high-risk boundaries when present. - Never invent cryptography or silently weaken a requirement to make a test pass. - Use provider interfaces for external services and deterministic fakes in tests. - Add migrations and rollback or recovery notes for persistent data changes. - Log useful operational context without credentials, tokens, passwords, or personal data. - Update documentation and run all checks before completing a milestone.
# Delivery milestones ## M0 — Decisions and scaffold - Confirm the runtime, persistence model, threat boundaries, and deployment target. - Create a reproducible local environment and continuous checks. ## M1 — Core workflow - Implement the smallest end-to-end product path with validation and tests. - Keep integrations behind interfaces. ## M2 — Trust layer - Add secure failure behavior, recovery paths, audit-relevant events, and data safeguards. - Test abuse cases and destructive operations. ## M3 — Operability - Add structured logs, error reporting hooks, health signals, backup/restore documentation, and deployment configuration. ## M4 — Release gate - Run a clean-install test, critical-path end-to-end test, dependency review, and documented rollback exercise. - Compare the shipped behavior with `PRODUCT.md` and publish remaining limitations.
# Operations ## Before release - Validate configuration and secrets at startup. - Define backup, restore, and rollback procedures and test them. - Document logs, error tracking, health signals, and alert ownership. - Set dependency update and vulnerability review expectations. ## Incident checklist 1. Contain the issue without destroying evidence or user data. 2. Record the timeline and affected scope. 3. Rotate exposed secrets and revoke compromised sessions or credentials. 4. Restore from a verified source when needed. 5. Document the root cause, remediation, and regression test. ## Launch constraint Do not market omitted Surfer SEO capabilities as implemented. The v1 non-goals in `PRODUCT.md` remain user-visible limitations until they are deliberately delivered.
$ choose a build depth, inspect the files, then open the complete pack in your agent · this prompt is generated from the build plan · improve it via PR
They pay because content optimization needs repeatable data and an editor that writers will use.
xSERP data reliability
xscoring model
xeditor UX
xAI article workflows
xintegrations
xaudits
xsupport
Nothing worth pointing at. That's why the prompt exists.
Surfer SEO pricing
| plan | monthly | annual (per mo) | what you get |
|---|---|---|---|
| discovery | $59/workspace | $49/workspace | 120 documents/year; 10 tracked pages; 1 brand workspace; 1 seat. |
| standard | $119/workspace | $99/workspace | 360 documents/year; 25 AI Search prompts/week; 50 tracked pages; 1 brand workspace; 3 seats. |
| pro | $219/workspace | $182/workspace | 360 documents/year; 50 AI Search prompts/day; 5 brand workspaces; 200 tracked pages; 5 seats. |
| peace of mind | $359/workspace | $299/workspace | Unlimited documents under fair use; 100 AI Search prompts/day; unlimited brand workspaces; 500 tracked pages; 10 seats; API access. |
| ai search analytics | $185/workspace | $158/workspace | 100 prompts/day; 5 brand workspaces. |
| enterprise | $999/workspace | — | Starts at $999/month with custom documents, prompts, workspaces, tracked pages, seats, API, security, and support. |
free tierno standing free tier; a trial/start-free path is offered, but public duration and numeric caps were not verified
billingmonthly + annual
hidden costsThe 'unlimited' document allowance is subject to fair use. AI Search Analytics capacity is sold separately or through dynamic prompt/workspace configurations.
verified 2026-08-14 · source ↗
Vibecode Surfer SEO
Kinda. The core of Surfer SEO is buildable in a weekend with the prompt on this page, but there are real gaps: SERP data reliability, scoring model. Read the honest list above before committing.
How much does Surfer SEO cost?
Surfer SEO costs about $99/month (Essential/Standard, checked 2026-07-30), which is $1188 per year.
What do I lose by replacing Surfer SEO?
Honestly: SERP data reliability; scoring model; editor UX; AI article workflows; integrations; audits; support. If any of those are load-bearing for you, keep paying.
Is there an open-source alternative to Surfer SEO?
No mature open-source alternative worth pointing at, which is exactly why the one-shot prompt on this page exists.