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Agent skill

Algo SEO Content

by asgard-ai-platform in asgard-ai-platform/skills

Execute content SEO strategy from keyword research through content planning, writing, and on-page optimization.

MITAuto-check passedMarketing & SEO

Install Algo SEO Content

skills CLI
$ npx skills add asgard-ai-platform/skills --skill algo-seo-content -a claude-code

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

GitHub CLI
$ gh skill install asgard-ai-platform/skills algo-seo-content --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/asgard-ai-platform/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/algo-seo-content .claude/skills/algo-seo-content && 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
algo-seo-content
GitHub stars
242
Token cost
~1.2k tokens
SKILL.md length
434 words
Files
4 (incl. references)
Skills in repo
207
Repo updated
First seen
Licence
MIT

At a glance

Execute content SEO strategy from keyword research through content planning, writing, and on-page optimization.

  • Works in 4 steps: Input Validation → Core Algorithm → Verification → …
  • The user needs to create SEO-optimized content
  • SKILL.md covers Overview, When to Use, Algorithm and Output Format, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Algo SEO Content is an agent skill from asgard-ai-platform/skills. Execute content SEO strategy from keyword research through content planning, writing, and on-page optimization. Use this skill when the user needs to create SEO-optimized content, perform keyword research, identify content gaps, or improve existing content rankings — even if they say 'content strategy', 'keyword research', or 'how to rank for this topic'.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `examples/sample_scenario.md`, `references/content-brief-template.md` and `references/keyword-clustering.md`).

It sits in Marketing & SEO, covering Keyword research, Content strategy and On-page SEO. The repository describes itself as: 301 open-source coding agent skills across 22 domains — methodology, judgment & gotchas packaged as Claude Agent Skills for the Asgard AI Platform. The licence is MIT.

When your agent uses it

  • The user needs to create SEO-optimized content
  • Perform keyword research
  • Identify content gaps
  • Improve existing content rankings — even if they say content strategy

Example prompts

  • “content strategy”
  • “keyword research”
  • “how to rank for this topic”
  • “/algo-seo-content”

Workflow steps

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

  1. Input Validation
  2. Core Algorithm
  3. Verification
  4. Output

What it can do on your machine

Read from SKILL.md and the folder at commit 4e7f4f8. 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 (its code samples are json).

    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

Algo SEO Content loads about 1.2k tokens when it runs, and up to ~5.4k if it reads all its reference files. Until then it costs about 94 tokens; SKILL.md has 434 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~94
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
~5.4k

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 asgard-ai-platform/skills at commit 4e7f4f8, republished under its MIT licence (© asgard-ai-platform). 434 words, ~1,172 tokens.

Download SKILL.mdSave it as .claude/skills/algo-seo-content/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
algo-seo-content
description
Execute content SEO strategy from keyword research through content planning, writing, and on-page optimization. Use this skill when the user needs to create SEO-optimized content, perform keyword research, identify content gaps, or improve existing content rankings — even if they say 'content strategy', 'keyword research', or 'how to rank for this topic'.
metadata.category
WP-35 SEO 演算法
metadata.tags
seo, content-strategy, keyword-research, on-page-seo

Content SEO Strategy

Overview

Content SEO is the systematic process of creating and optimizing content to match search intent and rank organically. The pipeline: keyword research → intent mapping → content creation → on-page optimization → performance monitoring. Success depends on intent match, not keyword density.

When to Use

Trigger conditions:

  • Planning new content to capture organic search traffic
  • Optimizing existing underperforming content
  • Conducting keyword research and content gap analysis

When NOT to use:

  • When the issue is technical (page speed, crawlability) — use technical SEO
  • When the issue is off-page (backlinks, authority) — use backlink analysis

Algorithm

IRON LAW: Content Must Match SEARCH INTENT
A perfectly optimized page targeting the wrong intent will NOT rank.
Four intent types:
1. Informational — wants to learn ("how to", "what is")
2. Navigational — wants a specific site ("github login")
3. Commercial — comparing options ("best CRM 2025")
4. Transactional — wants to buy/do ("buy iPhone 16 case")
Check SERP results to determine actual intent before writing.
Phase 1: Input Validation

Define target topic/niche. Gather seed keywords from brainstorming, competitor analysis, and tools (Ahrefs, SEMrush, Google Keyword Planner). Gate: Seed keyword list with search volume and difficulty estimates.

Phase 2: Core Algorithm
  1. Keyword clustering: Group related keywords by intent and topic
  2. SERP analysis: Check top 10 results for each cluster — identify intent, content format, and depth
  3. Content gap analysis: Find keywords competitors rank for that you don't
  4. Content brief: Define: target keyword, intent, format (guide/list/comparison), word count benchmark, required subtopics from SERP analysis
  5. On-page optimization: Title tag (keyword front-loaded), meta description, H1/H2 structure, internal links, image alt text
Phase 3: Verification

Check: title contains primary keyword, intent matches SERP, all key subtopics covered, internal links to related content. Gate: Content matches identified intent and covers SERP-derived subtopics.

Phase 4: Output

Return content brief and optimization checklist.

Output Format

json
{
  "content_brief": {"primary_keyword": "...", "intent": "informational", "format": "how-to guide", "target_word_count": 2000, "subtopics": ["...", "..."]},
  "optimization": {"title": "...", "meta_description": "...", "h2_structure": ["...", "..."], "internal_links": 5},
  "metadata": {"search_volume": 2400, "keyword_difficulty": 35}
}

Examples

Sample I/O

Input: Topic "email marketing automation", target market: Taiwan SMBs Expected: Primary KW: "email行銷自動化", intent: commercial investigation, format: comparison guide, 2500 words

Show full SKILL.md (172 more words)Show less
Edge Cases
InputExpectedWhy
Zero search volume keywordConsider if it's emerging or nonexistentMay be worth targeting if topically relevant
KD > 80 for new siteTarget long-tail variants firstNew sites can't compete on high-KD terms
Mixed intent SERPCreate content matching dominant intentDon't try to serve all intents in one page

Gotchas

  • Keyword density is dead: There's no optimal keyword density. Write naturally. Forced keyword insertion hurts readability and may trigger spam signals.
  • Search volume ≠ traffic: A #1 ranking for a 10K volume keyword won't bring 10K visits. Click-through rates vary by SERP features (ads, featured snippets, PAA).
  • Content freshness: Some queries demand fresh content (e.g., "best laptop 2025"). Outdated content drops rankings even if it once ranked #1.
  • Cannibalization: Multiple pages targeting the same keyword compete with each other. One strong page outperforms three mediocre ones.
  • E-E-A-T: For YMYL topics (health, finance), Google requires demonstrated Experience, Expertise, Authority, and Trust. Anonymous content won't rank.

References

  • For keyword clustering methodology, see references/keyword-clustering.md
  • For content brief templates, see references/content-brief-template.md

© asgard-ai-platform, MIT. 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 3 other files (references) in algo-seo-content of asgard-ai-platform/skills.

  • SKILL.md
  • examples/sample_scenario.md
  • references/content-brief-template.md
  • references/keyword-clustering.md

Open the folder on GitHubat commit 4e7f4f8

Compare with similar skills

Algo SEO Content 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.

Algo SEO Content compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Algo SEO Content this skillasgard-ai-platform/skills242—~1.2kAutomated safety check: PassMIT
SEO Keyword ClusteringAgriciDaniel/claude-seo19k2 repos~3.3kAutomated safety check: PassMIT
SEO Content Brief GeneratorAgriciDaniel/claude-seo19k2 repos~2.6kAutomated safety check: PassMIT
SEO Content Briefseranking/seo-skills161—~2.5kAutomated safety check: PassMIT
Blog OutlineAgriciDaniel/claude-blog2.3k1 repos~1.5kAutomated safety check: PassMIT
SEO Keyword Clusterseranking/seo-skills161—~2.5kAutomated safety check: PassMIT

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  • SEO Keyword Clustering

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Categories

Questions about Algo SEO Content

What does Algo SEO Content do?

Execute content SEO strategy from keyword research through content planning, writing, and on-page optimization. Algo SEO Content is an agent skill from asgard-ai-platform/skills. Execute content SEO strategy from keyword research through content planning, writing, and on-page optimization.

When should I use Algo SEO Content?

Algo SEO Content fits situations like: the user needs to create SEO-optimized content; perform keyword research; identify content gaps; improve existing content rankings — even if they say content strategy.

How do I install Algo SEO Content in Claude Code?

Run `npx skills add asgard-ai-platform/skills --skill algo-seo-content -a claude-code`. Or copy the skill folder (algo-seo-content in asgard-ai-platform/skills) into .claude/skills/algo-seo-content in your project. Claude Code loads it when a task matches its description.

How do I install Algo SEO Content in Codex?

Run `npx skills add asgard-ai-platform/skills --skill algo-seo-content -a codex`. Or copy the skill folder (algo-seo-content in asgard-ai-platform/skills) into .agents/skills/algo-seo-content in your project. Codex loads it when a task matches its description.

Can I use Algo SEO Content 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 asgard-ai-platform/skills --skill algo-seo-content -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/algo-seo-content, .gemini/skills/algo-seo-content, .github/skills/algo-seo-content and .opencode/skills/algo-seo-content in your project.

What does Algo SEO Content need to run?

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

Does Algo SEO Content 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 Algo SEO Content 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 Algo SEO Content use?

Algo SEO Content is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Algo SEO Content use?

About 1.2k tokens (SKILL.md is roughly 4.7k 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 4.3k tokens, read only when the agent opens those files.

What are the alternatives to Algo SEO Content?

Skills that share tags, products or a category with Algo SEO Content: SEO Keyword Clustering (AgriciDaniel/claude-seo, 19k stars), SEO Content Brief Generator (AgriciDaniel/claude-seo, 19k stars), SEO Content Brief (seranking/seo-skills, 161 stars) and Blog Outline (AgriciDaniel/claude-blog, 2.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Algo SEO Content?

asgard-ai-platform (a GitHub organization) maintains it in asgard-ai-platform/skills, which has 242 GitHub stars. The repository holds 207 skills in this directory. The repository was last updated on June 6, 2026.

Source: asgard-ai-platform/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.