SEO Content Brief Generator
AgriciDaniel/claude-seo
Builds research-backed SEO content briefs with competitor scoring, per-section word counts and page-type templates, for new pages or improving existing ones.
Competitive landscape analysis: positioning, scorecards, moat assessment, market share trends.
$ npx skills add ginlix-ai/LangAlpha --skill competitive-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ginlix-ai/LangAlpha competitive-analysis --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/ginlix-ai/LangAlpha.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/langalpha_research/skills/competitive-analysis .claude/skills/competitive-analysis && rm -rf skills-srcUse ~/.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/
Install the "competitive-analysis" agent skill from https://github.com/ginlix-ai/LangAlpha/tree/main/plugins/langalpha_research/skills/competitive-analysis into .claude/skills/competitive-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "competitive-analysis", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/ginlix-ai/LangAlpha/tree/main/plugins/langalpha_research/skills/competitive-analysisType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add ginlix-ai/LangAlpha --skill competitive-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ginlix-ai/LangAlpha competitive-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ginlix-ai/LangAlpha.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/langalpha_research/skills/competitive-analysis .agents/skills/competitive-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "competitive-analysis" agent skill from https://github.com/ginlix-ai/LangAlpha/tree/main/plugins/langalpha_research/skills/competitive-analysis into .agents/skills/competitive-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "competitive-analysis", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ginlix-ai/LangAlpha --skill competitive-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ginlix-ai/LangAlpha competitive-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ginlix-ai/LangAlpha.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/langalpha_research/skills/competitive-analysis .cursor/skills/competitive-analysis && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "competitive-analysis" agent skill from https://github.com/ginlix-ai/LangAlpha/tree/main/plugins/langalpha_research/skills/competitive-analysis into .cursor/skills/competitive-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "competitive-analysis", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/ginlix-ai/LangAlpha.git --path plugins/langalpha_research/skills/competitive-analysis--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add ginlix-ai/LangAlpha --skill competitive-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ginlix-ai/LangAlpha competitive-analysis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ginlix-ai/LangAlpha.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/langalpha_research/skills/competitive-analysis .gemini/skills/competitive-analysis && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "competitive-analysis" agent skill from https://github.com/ginlix-ai/LangAlpha/tree/main/plugins/langalpha_research/skills/competitive-analysis into .gemini/skills/competitive-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "competitive-analysis", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install ginlix-ai/LangAlpha competitive-analysisInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add ginlix-ai/LangAlpha --skill competitive-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ginlix-ai/LangAlpha.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/langalpha_research/skills/competitive-analysis .github/skills/competitive-analysis && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "competitive-analysis" agent skill from https://github.com/ginlix-ai/LangAlpha/tree/main/plugins/langalpha_research/skills/competitive-analysis into .github/skills/competitive-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "competitive-analysis", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ginlix-ai/LangAlpha --skill competitive-analysis -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ginlix-ai/LangAlpha competitive-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ginlix-ai/LangAlpha.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/langalpha_research/skills/competitive-analysis .opencode/skills/competitive-analysis && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "competitive-analysis" agent skill from https://github.com/ginlix-ai/LangAlpha/tree/main/plugins/langalpha_research/skills/competitive-analysis into .opencode/skills/competitive-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "competitive-analysis", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
competitive-analysisCompetitive landscape analysis: positioning, scorecards, moat assessment, market share trends.
Competitive Analysis is an agent skill from ginlix-ai/LangAlpha. Competitive landscape analysis: positioning, scorecards, moat assessment, market share trends. Triggers on competitive analysis, competitive landscape, competitor benchmarking, moat assessment, market share, who are the competitors.
Its SKILL.md is about 3.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `references/frameworks.md`, `references/presentation.md` and `references/schemas.md`).
It sits in Marketing & SEO, covering Competitor analysis. The repository describes itself as: Claude Code for Financial Market. The licence is Apache-2.0.
10 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit e05bd91. It shows what the files ask for, not the result of running them.
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.
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.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Competitive Analysis loads about 3.1k tokens when it runs, and up to ~6.3k if it reads all its reference files. Until then it costs about 63 tokens; SKILL.md has 1,676 words of instructions outside code blocks.
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.
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.
The full file from ginlix-ai/LangAlpha at commit e05bd91, republished under its Apache-2.0 licence (© ginlix-ai). 1,676 words, ~3,131 tokens.
.claude/skills/competitive-analysis/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.Who competes, on what, and which advantages survive. The product is a comparison, so the comparison has to be real: same period, same metric definition, same basis, with each figure's provenance visible. A table of numbers that were measured differently looks like analysis and is not one.
Evidence labels, source tiers, staleness, the readiness posture and the intake limits: .agents/skills/research-conventions/SKILL.md, read before the first deliverable.
.agents/skills/competitive-analysis/references/presentation.md..agents/skills/competitive-analysis/references/unit-economics.md, which carries the benchmark bands (Rule of 40 on EBITDA margin, NDR, LTV:CAC, CAC payback), the cohort matrix and the traps that make two companies look comparable when they are not..agents/skills/competitive-analysis/references/schemas.md..agents/skills/competitive-analysis/references/frameworks.md.These bind every run, whatever the deliverable is.
Each cell in a competitor table carries the figure, its as-of, and one label from the closed set in .agents/skills/research-conventions/references/evidence.md, which also holds the freshness thresholds and the six staleness states. Three of the seven carry most of a competitor table: fact for the company's own filed statements, company claim for a management figure that is not in them (market share, customer count, addressable market), and street estimate for a consensus or single-analyst number, with its vintage and analyst count.
A third-party sizing of a private company is a street estimate: fact is reserved for a primary document or a data-tool figure for a period that has closed. A research house's published sizing carries the house as its estimator and the publication date as its vintage, and anything with no traceable publisher stays needs-source until one is found.
The as-of is the fiscal period for a reported figure, the publication date for an estimate, and the retrieval date for anything built on price. A private-company figure carries a label and an as-of like any other cell, and prints the reader-facing word its label maps to in .agents/skills/research-conventions/references/evidence.md.
Label the gap rather than filling it. The cell reads not disclosed, and the table note says what was searched. Where the missing metric is load-bearing, meaning the ranking or the moat conclusion moves without it, take one of the two exits in the unsupported-claim rule: drop the conclusion that rests on it, or carry a bound ("the range consistent with the reported total is A to B"), label it assumption, and re-read the posture from the ladder in .agents/skills/research-conventions/SKILL.md against the new input state. A plausible-looking estimate with no flag is exactly the failure that rule exists to catch: evidence.md.
.agents/skills/research-conventions/references/market-data-rules.md.not disclosed per the gap rule in Step 1.[Company] [Document] ([Date]).Where a source file and a filing disagree, the conflict register in evidence.md decides it and the artifact shows the selection.
The general tiers by claim family are in evidence.md and govern. Two additions specific to this work: sell-side research is the usual route to a private competitor's size and is a street estimate with its vintage, and industry research houses are the usual route to a share figure and carry the house and the publication date.
Default working analysis: 8 to 12 pages, or 12 to 20 slides, plus the comparison workbook. A rapid competitive read is a first pass at up to five slides. Bands and cut order: .agents/skills/research-conventions/references/depth.md.
Phase 1, scope it. Confirm: single-company deep dive or multi-company comparison; deck or written memo; the specific competitors, dimensions or strategic question in play; whether an investment context needs scenarios and signposts; and which source files exist and which values come out of them.
Phase 2, research, outline, review, build. Run Steps 0 through 9 below, show the outline with the real numbers already in it, and build the final artifact after the outline has been reviewed. That review is an intake exception and yields under .agents/skills/research-conventions/references/intake.md: when this skill runs as an input to another workflow, or the user asked for the finished artifact in one request, present the outline and keep building without waiting on it.
Before any pull, name the three to five metrics this industry is actually judged on:
| Industry | Key metrics |
|---|---|
| SaaS | ARR, NRR, CAC payback, LTV/CAC, Rule of 40 on EBITDA margin |
| Payments | GPV, take rate, attach rate, transaction margin |
| Marketplaces | GMV, take rate, buyer/seller ratio, repeat rate |
| Retail | Same-store sales, inventory turns, sales per square foot |
| Logistics | Volume, cost per unit, on-time delivery, capacity utilisation |
For an industry not listed, take the three to five metrics investors and operators use to benchmark it. Use the same set for every company in the comparison.
Market size now and projected, with the source and its vintage. Growth drivers, headwinds, and the trends reshaping the industry.
Correct: "The embedded payments market is $80B to $100B in 2024, growing 20% to 25% a year (research house, 2024)." Not usable: "The market is large and growing rapidly."
Map where the value flows, in the shape the industry actually has:
| Metric | Value | As-of | Label |
|---|---|---|---|
| Revenue | $4.96B | FY2024 | fact |
| Growth | +26% y/y | FY2024 | fact |
| Gross margin | 45% | FY2024 | fact |
| Profitability | $373M adj. EBITDA | FY2024 | fact |
| Customers | 134K | Q4 FY2024 | company claim |
| Retention | 92% | Q4 FY2024 | company claim |
| Market share | ~15% | 2024 | street estimate |
For a multi-segment company, add the segment breakdown:
| Segment | Revenue | Rev y/y | Rev % | EBITDA | EBITDA y/y | Margin |
|---|---|---|---|---|---|---|
| Seg A | $25.1B | +26% | 57% | $6.5B | +31% | 26% |
| Seg B | $13.8B | +31% | 31% | $2.5B | +64% | 18% |
| Seg C | $5.1B | -2% | 12% | -$74M | -16% | -1% |
| Total | $44.0B | +18% | 100% | $6.5B | 15% |
Note unallocated corporate costs where the segments do not foot to the total.
Group the set with whichever cut is real for this industry: by business model (platform, vertical, horizontal), by segment served (enterprise, SMB, consumer), by posture (direct, adjacent, emerging), or by origin (incumbent, disruptor, new entrant).
| Visualisation | Best for |
|---|---|
| 2x2 matrix | Two dominant competitive factors |
| Radar | Multi-factor comparison |
| Tier diagram | Natural clustering into strategic groups |
| Value chain map | Vertical industries |
| Ecosystem map | Platform markets |
Metrics, on the Step 0 set, each row carrying its as-of and label as in Step 3.
Qualitative:
| Category | Assessment |
|---|---|
| Business | What they do, one sentence |
| Strengths | Two or three bullets |
| Weaknesses | Two or three bullets |
| Strategy | Current priorities |
| Dimension | Company A | Company B | Company C |
|---|---|---|---|
| Scale | ●●● $160B | ●●○ $45B | ●○○ $8B |
| Growth | ●●○ +26% | ●●● +35% | ●●○ +22% |
| Margins | ●●○ 7.5% | ●○○ 3.2% | ●●● 15% |
Row-merge discipline. Two competitors share a row only where "Row-merge discipline" in .agents/skills/research-conventions/references/judgment.md allows it.
M&A transactions with their multiples and the strategic logic, partnership and integration patterns, capital-raising activity, and regulatory developments.
Moat assessment. The rating is a judgement and is written as one: each row shows what was observed, then what we conclude from it.
| Moat type | Observed | Rating | Why the observation supports it |
|---|---|---|---|
| Network effects | the flywheel evidence, cross-side or same-side | Strong / Moderate / Weak | one clause |
| Switching costs | integration depth, contractual lock-in, habit | ||
| Scale economies | unit cost at volume, minimum efficient scale | ||
| Intangible assets | brand, proprietary data, licences, patents |
A Strong with an empty observed column is an opinion in a table. Keep the observation and the rating in separate columns so a reader can disagree with the second while keeping the first. How far the evidence lets the language go: evidence.md.
Then three things: the durable advantages, mapped to the rows above; the structural vulnerabilities that are hard to fix; and the current state against the trajectory, which is where the two diverge.
For an investment context:
| Scenario | Probability | Key driver |
|---|---|---|
| Bull | 30% | Share gains, margin expansion |
| Base | 50% | Current trajectory continues |
| Bear | 20% | Competitive pressure, margin compression |
The probability set follows "Probabilities" in .agents/skills/research-conventions/references/judgment.md, and each scenario names the competitive driver that produces it.
Verify before delivery. Deck and document formatting has its own checklist in .agents/skills/competitive-analysis/references/presentation.md.
Comparability
Provenance
[Company] [Document] ([Date]) form.not disclosed with a table note saying what was searched, and no cell holds an unlabelled estimate.Analysis
© ginlix-ai, 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
SKILL.md and 4 other files (references) in plugins/langalpha_research/skills/competitive-analysis of ginlix-ai/LangAlpha.
Open the folder on GitHubat commit e05bd91
Competitive Analysis 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Competitive Analysis this skillginlix-ai/LangAlpha | 1.8k | — | ~3.1k | Automated safety check: Pass | Apache-2.0 | |
| SEO Content Brief GeneratorAgriciDaniel/claude-seo | 19k | 2 repos | ~2.6k | Automated safety check: Pass | MIT | |
| SEO DataforseoAgriciDaniel/codex-seo | 797 | 2 repos | ~4.6k | Automated safety check: Pass | MIT | |
| Competitor ProfilingNexus-JPF/note-companion | 870 | 4 repos | ~3.5k | Automated safety check: Pass | MIT | |
| Startup Competitorsferdinandobons/startup-skill | 1.2k | — | ~4.1k | Automated safety check: Pass | MIT | |
| Amazon Listing Competitor Analysisbrowser-act/skills | 6.1k | 1 repos | ~3.2k | Automated safety check: Pass | MIT |
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Categories
Competitive landscape analysis: positioning, scorecards, moat assessment, market share trends. Competitive Analysis is an agent skill from ginlix-ai/LangAlpha. Competitive landscape analysis: positioning, scorecards, moat assessment, market share trends.
Competitive Analysis fits situations like: competitive analysis; competitive landscape; competitor benchmarking; moat assessment.
Run `npx skills add ginlix-ai/LangAlpha --skill competitive-analysis -a claude-code`. Or copy the skill folder (plugins/langalpha_research/skills/competitive-analysis in ginlix-ai/LangAlpha) into .claude/skills/competitive-analysis in your project. Claude Code loads it when a task matches its description.
Run `npx skills add ginlix-ai/LangAlpha --skill competitive-analysis -a codex`. Or copy the skill folder (plugins/langalpha_research/skills/competitive-analysis in ginlix-ai/LangAlpha) into .agents/skills/competitive-analysis in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ginlix-ai/LangAlpha --skill competitive-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/competitive-analysis, .gemini/skills/competitive-analysis, .github/skills/competitive-analysis and .opencode/skills/competitive-analysis in your project.
SKILL.md names no scripts, command-line tools or credentials: Competitive Analysis is instructions for the agent only.
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.
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.
Competitive Analysis 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.
About 3.1k tokens (SKILL.md is roughly 13k 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 3.2k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Competitive Analysis: SEO Content Brief Generator (AgriciDaniel/claude-seo, 19k stars), SEO Dataforseo (AgriciDaniel/codex-seo, 797 stars), Competitor Profiling (Nexus-JPF/note-companion, 870 stars) and Startup Competitors (ferdinandobons/startup-skill, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
ginlix-ai (a GitHub organization) maintains it in ginlix-ai/LangAlpha, which has 1,811 GitHub stars. The repository holds 37 skills in this directory. The repository was last updated on October 9, 2026.
Source: ginlix-ai/LangAlpha on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.