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Agent skill

Run SEO Page Loop

by tsingyuai in tsingyuai/growth-lab

Run an SEO page observation-action-review loop with persistent Memory by coordinating demand research, page creation, adversarial review, image generation, IndexNow submission, and performance review.

Apache-2.0Auto-check passedAgent Workflows

Install Run SEO Page Loop

skills CLI
$ npx skills add tsingyuai/growth-lab --skill run-seo-page-loop -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install tsingyuai/growth-lab run-seo-page-loop --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/tsingyuai/growth-lab.git skills-src && mkdir -p .claude/skills && cp -r skills-src/models/run-seo-page-loop .claude/skills/run-seo-page-loop && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
run-seo-page-loop
GitHub stars
2k
Token cost
~1.2k tokens
SKILL.md length
586 words
Files
3 (incl. references)
Skills in repo
22
Repo updated
First seen
Licence
Apache-2.0

At a glance

Run an SEO page observation-action-review loop with persistent Memory by coordinating demand research, page creation, adversarial review, image generation, IndexNow submission, and performance review.

  • Works in 6 steps: Read Memory → Observe → Decide → …
  • Taking an SEO page from opportunity discovery through publication
  • SKILL.md covers Boundaries, 1. Read Memory, 2. Observe and 3. Decide, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Run SEO Page Loop is an agent skill from tsingyuai/growth-lab. Run an SEO page observation-action-review loop with persistent Memory by coordinating demand research, page creation, adversarial review, image generation, IndexNow submission, and performance review. Use when taking an SEO page from opportunity discovery through publication, measurement, iteration, or continuing a previous SEO loop from Memory.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `agents/openai.yaml` and `references/memory.md`).

It sits in Agent Workflows, covering Agent memory, Performance reviews and Image generation. The repository describes itself as: An end-to-end growth tool that understands the product, fetch the data it needs, researches the market, executes campaigns, and reviews results to improve the next round of… The licence is Apache-2.0.

When your agent uses it

  • Taking an SEO page from opportunity discovery through publication
  • Continuing a previous SEO loop from Memory

Example prompts

  • “/run-seo-page-loop”

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Read Memory
  2. Observe
  3. Decide
  4. Act
  5. Review
  6. Write Memory and continue

What it can do on your machine

Read from SKILL.md and the folder at commit 2d0807c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Run SEO Page Loop loads about 1.2k tokens when it runs, and up to ~1.6k if it reads all its reference files. Until then it costs about 91 tokens; SKILL.md has 586 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~91
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from tsingyuai/growth-lab at commit 2d0807c, republished under its Apache-2.0 licence (© tsingyuai). 586 words, ~1,223 tokens.

Download SKILL.mdSave it as .claude/skills/run-seo-page-loop/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
run-seo-page-loop
description
Run an SEO page observation-action-review loop with persistent Memory by coordinating demand research, page creation, adversarial review, image generation, IndexNow submission, and performance review. Use when taking an SEO page from opportunity discovery through publication, measurement, iteration, or continuing a previous SEO loop from Memory.

Run the SEO page loop

Coordinate the loop inside the product workspace. Let the current Codex or Claude Code session control the work. Use memory/run-seo-page-loop/ as this Model's persistent Memory.

text
Read Memory → Observe → Decide → Act → Review → Write Memory → Next observation

Read memory.md before starting. Recover relevant observations, actions, outcomes, conclusions, and next-action recommendations.

Boundaries

  • Keep this Model focused on when and why the loop moves between observation, decision, action, and review.
  • Delegate data-collection methods and source-specific interpretation to Collectors.
  • Delegate creation, implementation, publishing, inspection, and performance-review techniques to Executors.
  • Use Runtime-native browser, search, page inspection, screenshot, and local web-testing capabilities directly.
  • Add a Client only for an external API action the Runtime cannot perform natively.
  • Create no fixed schema, database, dashboard, workflow state, or task queue.
  • Store dated operational evidence, analysis, outcomes, and next-action recommendations in Memory.
  • Apply improvements to the loop itself directly to this Model. Keep methodology-change suggestions out of Memory.

1. Read Memory

Read recent Memory entries and older entries relevant to the product, page, query family, or pending action. Establish what is already known, what was attempted, what happened, and which recommendation should now be tested.

2. Observe

Invoke $research-seo-demand to collect and interpret current search demand and live SERP evidence. Combine it with product context and relevant Memory.

When the loop begins from an existing page, invoke $review-seo-performance first to observe its current outcome.

Persist useful raw evidence and a dated observation in memory/run-seo-page-loop/.

3. Decide

Before choosing a page action, confirm that the current observation contains a competitor-page breakdown for every candidate query being considered. The breakdown must cover three to five relevant leading pages and include:

  • each page's search presentation and winning page shape;
  • a top-to-bottom description of its visible blocks;
  • reading and conversion hooks, information density, user value, and tone;
  • evidence, unique information, authorship, and negative quality signals;
  • an information-gain gap synthesized across the leading pages.

Do not invoke $create-seo-page from keyword volume, result snippets, or a list of ranking URLs alone. When this evidence is absent, return to Observe and complete it with $research-seo-demand.

Choose one action supported by current evidence and historical Memory. State the expected observable result and the evidence that would confirm or challenge the decision.

Possible actions include creating a page, improving an existing page, changing its snippet, strengthening evidence, adjusting conversion, resolving discovery problems, creating a supporting page, or waiting for a defined observation window.

Show full SKILL.md (197 more words)Show less

4. Act

Coordinate the relevant Executors:

  1. Invoke $create-seo-page to design and implement the page.
  2. Invoke $generate-image when the page needs a generated or edited asset.
  3. Invoke $review-seo-page before release and apply accepted fixes.
  4. Use the product's own checks and Runtime-native browser testing.
  5. Deploy through the product's existing release process.
  6. After the live URL is publicly accessible, submit it with executors/indexnow/submit-indexnow.mjs.

Record the action, live URL, launch time, target intent, and baseline evidence in Memory.

5. Review

At the appropriate observation time, invoke $review-seo-performance. Compare current evidence with the baseline and previous Memory. Determine whether the action improved discovery, ranking, click-through, intent fit, content usefulness, product outcomes, or AI visibility.

Invoke $review-seo-page again when performance evidence points to a page-quality or intent problem.

6. Write Memory and continue

Write the dated operational evidence, analysis, summary, outcome, and recommended next action to memory/run-seo-page-loop/. Link the entry to the earlier observation or action it evaluates.

When the run reveals a better loop, edit this Model's SKILL.md or references/memory.md directly. Record the real operational outcome in Memory and the improved method in the Model.

Return the selected next action to the beginning of the loop.

© tsingyuai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in models/run-seo-page-loop of tsingyuai/growth-lab.

  • SKILL.md
  • agents/openai.yaml
  • references/memory.md

Open the folder on GitHubat commit 2d0807c

Compare with similar skills

Run SEO Page Loop next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Run SEO Page Loop compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Run SEO Page Loop this skilltsingyuai/growth-lab2k—~1.2kAutomated safety check: PassApache-2.0
Extract Visual Style 2ajinnaaa/extract-visual-style-2124—~2.3kAutomated safety check: PassMIT
Make FiguresAperivue/medsci-skills333—~8.4kAutomated safety check: PassMIT
Gemini SkillWJZ-P/gemini-skill832—~1.1kAutomated safety check: PassMIT
ComfyComfy-Org/comfy-skills222—~1.4kAutomated safety check: PassMIT
Authoring Skillsfriday-platform/friday-studio104—~2.4kAutomated safety check: PassCustom licence

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Categories

Questions about Run SEO Page Loop

What does Run SEO Page Loop do?

Run an SEO page observation-action-review loop with persistent Memory by coordinating demand research, page creation, adversarial review, image generation, IndexNow submission, and performance review. Run SEO Page Loop is an agent skill from tsingyuai/growth-lab. Run an SEO page observation-action-review loop with persistent Memory by coordinating demand research, page creation, adversarial review, image generation, IndexNow submission, and performance review.

When should I use Run SEO Page Loop?

Run SEO Page Loop fits situations like: taking an SEO page from opportunity discovery through publication; continuing a previous SEO loop from Memory.

How do I install Run SEO Page Loop in Claude Code?

Run `npx skills add tsingyuai/growth-lab --skill run-seo-page-loop -a claude-code`. Or copy the skill folder (models/run-seo-page-loop in tsingyuai/growth-lab) into .claude/skills/run-seo-page-loop in your project. Claude Code loads it when a task matches its description.

How do I install Run SEO Page Loop in Codex?

Run `npx skills add tsingyuai/growth-lab --skill run-seo-page-loop -a codex`. Or copy the skill folder (models/run-seo-page-loop in tsingyuai/growth-lab) into .agents/skills/run-seo-page-loop in your project. Codex loads it when a task matches its description.

Can I use Run SEO Page Loop in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add tsingyuai/growth-lab --skill run-seo-page-loop -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/run-seo-page-loop, .gemini/skills/run-seo-page-loop, .github/skills/run-seo-page-loop and .opencode/skills/run-seo-page-loop in your project.

What does Run SEO Page Loop need to run?

SKILL.md names no scripts, command-line tools or credentials: Run SEO Page Loop is instructions for the agent only.

Does Run SEO Page Loop access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Run SEO Page Loop safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Run SEO Page Loop use?

Run SEO Page Loop is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Run SEO Page Loop use?

About 1.2k tokens (SKILL.md is roughly 4.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 407 tokens, read only when the agent opens those files.

What are the alternatives to Run SEO Page Loop?

Skills that share tags, products or a category with Run SEO Page Loop: Extract Visual Style 2 (ajinnaaa/extract-visual-style-2, 124 stars), Make Figures (Aperivue/medsci-skills, 333 stars), Gemini Skill (WJZ-P/gemini-skill, 832 stars) and Comfy (Comfy-Org/comfy-skills, 222 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Run SEO Page Loop?

tsingyuai (a GitHub organization) maintains it in tsingyuai/growth-lab, which has 2,000 GitHub stars. The repository holds 22 skills in this directory. The repository was last updated on September 28, 2026.

Source: tsingyuai/growth-lab on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.