What does this skill do, and when should you use it?
geo-report is the closing skill in the 16-skill geo-seo-claude repository, living at skills/geo-report/SKILL.md. It performs no audits itself; instead it aggregates the output files of prerequisite skills (geo-platform-optimizer, geo-schema, geo-technical, geo-content, optionally geo-llmstxt and geo-brand-mentions) and computes a weighted composite GEO Readiness Score from 0 to 100. The report follows a fixed 12-section template — executive summary, AI visibility dashboard, AI crawler access, brand authority, citability analysis, technical health, prioritized action plan, and more — written for business owners rather than developers. The deliverable is a self-contained 3,000–6,000 word GEO-CLIENT-REPORT.md that can be sent to a client without editing.
Reads markdown audit outputs (GEO-PLATFORM-OPTIMIZATION.md, GEO-SCHEMA-REPORT.md, GEO-TECHNICAL-AUDIT.md, GEO-CONTENT-ANALYSIS.md, and optional files); computes the composite score as Platform 25% + Content/E-E-A-T 25% + Technical 20% + Schema 15% + Brand Authority 15%; maps the score to a five-tier client-facing label (Excellent through Needs Attention); fills a 12-section template covering per-platform readiness for Google AI Overviews, ChatGPT, Perplexity, Gemini, and Bing Copilot, access status for AI crawlers, brand entity presence on Wikipedia, Reddit, LinkedIn and others, and a timeline-based action table (quick wins / month / quarter) with conservative dollar-value estimates; writes GEO-CLIENT-REPORT.md as the final output.
- A GEO/SEO consultant who has finished a full audit and needs a polished, client-ready deliverable instead of raw technical data
- An agency that wants standardized scoring and a fixed 12-section template so multiple team members produce consistent reports
- A marketing lead who must translate technical gaps (missing SSR, blocked crawlers) into business impact for an executive audience
- A service provider building renewal conversations around a timeline action plan split into quick wins (<4h), medium-term (1–5 days), and strategic initiatives
- An analyst with competitor URLs who needs a side-by-side comparison table of AI platform readiness gaps
How do you install this skill?
- This is a static source review only; nothing was executed and confidence is low.
- The report template bakes in speculative revenue-impact figures ($X,XXX/month etc.); these must be manually verified and edited before client delivery or they may constitute misleading business claims.
- The skill fully depends on output files from upstream skills (geo-platform-optimizer, geo-schema, geo-technical, geo-content); behavior is undefined when those are missing or change format — run upstream audits first and verify the files exist.
- Brand authority analysis relies on Wikipedia, Reddit, LinkedIn and similar platforms that may be unreachable from mainland-China networks, potentially distorting conclusions.
- Citation statistics embedded in the template (47.9%, 46.7%, etc.) have no verifiable source within this repository; verify independently before use.
- Publisher is unverified by the FollowSkills registry and treated as unknown; assess maintenance continuity yourself.
- Shell / CLI
- Network access
- Local filesystem
Claude Code CLI for the bundled collection; the geo-report skill itself consumes markdown audit files produced by sibling skills (geo-platform-optimizer, geo-schema, geo-technical, geo-content, optionally geo-llmstxt and geo-brand-mentions)
Install the whole skill collection first: on macOS/Linux run curl -fsSL https://raw.githubusercontent.com/zubair-trabzada/geo-seo-claude/main/install.sh | bash; on Windows run install-win.sh from Git Bash. Requires Python 3.8+, Claude Code CLI, and Git; Python dependencies go into an isolated venv at ~/.claude/skills/geo/.venv/. This skill installs as part of the collection — no separate step is documented.
tmp="$(mktemp -d)"
git clone --depth 1 https://github.com/zubair-trabzada/geo-seo-claude.git "$tmp"
mkdir -p ~/.claude/skills
cp -R "$tmp/skills/geo-report" ~/.claude/skills/
rm -rf "$tmp"Generated from the source repository and skill path; it copies only this skill's folder. If the author's install steps above differ, follow those first. To scope it to one project, replace ~/.claude/skills with that project's .claude/skills.
How do you use this skill?
In Claude Code, first run the prerequisite audits (/geo platforms, /geo schema, /geo technical, /geo content, optionally /geo llmstxt and /geo brands) and confirm their output files exist; then run /geo report <url> to trigger this skill, or ask Claude to follow the template in skills/geo-report/SKILL.md directly. Output is GEO-CLIENT-REPORT.md. For a chart-rich PDF version, the repository ships a separate geo-report-pdf skill.
What are this skill's strengths and limitations?
- Explicitly written for business owners: technical findings are translated into business impact with no jargon or hedging
- Scoring weights and formula are public and deterministic, with five tiers each paired with client-readable interpretation copy
- Action plan is tiered by quick wins (<4 hours), medium-term (1–5 days), and strategic (weeks), with impact, effort, and affected platforms per item
- Built-in glossary and methodology appendix make the report self-contained and printable
- Mandates conservative estimates, explicit assumptions, and forbids guaranteeing specific results
- Performs no audits itself — if prerequisite audit files are missing or weak, the report cannot be generated accurately
- Dollar-value estimates (e.g., $X,XXX/month uplift) rest on industry benchmark inference not verifiable from the repo
- Third-party statistics cited in the template (e.g., '47.9% of ChatGPT citations are Wikipedia') come from external studies and cannot be verified in-repo
- Competitor comparison, llms.txt, and brand authority sections are optional; report completeness degrades without competitor URLs
- Prerequisite skill output filenames and formats must match exactly; no fallback behavior is documented for mismatches
- Output is markdown only; the PDF chart version requires the separate geo-report-pdf skill
How does this skill compare with similar options?
Side by side with related skills; every score comes from the same FSRS standard.
| Skill | FS score | Stars | Last updated | License |
|---|---|---|---|---|
| GEO Client Report Generator (geo-report) this page | 48 · Use with care | ★ 11k | 20d ago | MIT |
| llms.txt Analysis & Generation Skill | 46 · Use with care | ★ 11k | 20d ago | MIT |
| GEO Platform Optimizer | 44 · Not recommended | ★ 11k | 20d ago | MIT |
| SEOBuild Onpage (SEO-AGI) | 50 · Use with care | ★ 257 | 9d ago | — |
| GEO Full-Site Audit | 48 · Use with care | ★ 11k | 20d ago | MIT |
The repo positions traditional SEO tooling as being displaced by GEO (citing a Gartner forecast of a 50% search traffic drop by 2028) but names no specific competitor, so no comparison is fabricated here.
How did FollowSkills review this skill?
The skill only aggregates local upstream audit outputs and writes one markdown file; permissions (Read/Grep/Glob/Bash/WebFetch/Write) are roughly proportionate with no sign of data exfiltration; but Bash and WebFetch usage is unscoped, the template encourages speculative client-facing revenue-impact figures (e.g. estimated $X,XXX/month) that could mislead end clients without human review, and there is no rollback or data-flow disclosure.
The workflow, scoring formula and template are self-consistent; but the whole flow depends on four (or six) upstream skill output files existing in consistent formats, the skill lacks error handling for missing upstream files, and static review finds no executable test evidence for this skill's key path (repo tests cover only the shared fetch_page.py).
The target scenario (client-facing GEO report delivery) and output format (GEO-CLIENT-REPORT.md) are clear, with defined inputs; but capability boundaries and non-fit ranges are undeclared, there is no Chinese-language support statement, and the report leans heavily on platforms (Wikipedia, Reddit, etc.) that are hard to reach from mainland China networks.
SKILL.md has version, tags, frontmatter, a complete template and glossary, well layered; but no changelog, no known-limitations disclosure, no maintenance responsibility statement; the author field is a repository alias rather than a verifiable identity, and unrelated skool community marketing in the repo dilutes documentation quality.
The template is thorough (score tables, dashboards, action plan, glossary) and looks directly usable; but the "ready to send without editing" claim rests on upstream scores being correct and revenue estimates being credible, the built-in dollar-value framing requires human correction, and static review cannot verify full report quality — scores above the static anchor of 7 cannot be awarded.
The template embeds multiple statistics with no verifiable source in this repo ("47.9% of ChatGPT citations are Wikipedia", "46.7% of Perplexity citations are Reddit", "10-point improvement correlates with 15-25% citation increase"), citing only vaguely named industry studies; repo tests do not cover this skill path, so static evidence is thin.
Open a dimension to read why it scored that way
Evidence confidence：Low — Mostly static review, author material or a limited demo; useful for discovery, not high-risk decisions.
See the full review method →