Tencent SkillHub · Data Analysis

GEO Performance Report Builder

Build comprehensive GEO performance reports with executive summaries, platform breakdowns, competitive analysis, and strategic action plans. Use whenever the...

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High Signal

Build comprehensive GEO performance reports with executive summaries, platform breakdowns, competitive analysis, and strategic action plans. Use whenever the...

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Install for OpenClaw

Quick setup

Download the package from Yavira.
Extract the archive and review SKILL.md first.
Import or place the package into your OpenClaw setup.

Requirements

Target platform: OpenClaw
Install method: Manual import
Extraction: Extract archive
Prerequisites: OpenClaw
Primary doc: SKILL.md

Package facts

Download mode: Yavira redirect
Package format: ZIP package
Source platform: Tencent SkillHub
What's included: SKILL.md, scripts/build_report.py, references/structure-guide.md, evals/evals.json

Validation

Use the Yavira download entry.
Review SKILL.md after the package is downloaded.
Confirm the extracted package contains the expected setup assets.

Install with your agent

Agent handoff

Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.

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New install

I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.

Upgrade existing

I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.

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Trust & source

Release facts

Source: Tencent SkillHub
Verification: Indexed source record
Version: 1.0.0

Provenance

Publisher: geoly-geo
Source page: View original listing
Canonical URL: Open canonical page

Documentation

ClawHub primary doc Primary doc: SKILL.md 9 sections Open source page

GEO Report Builder

Methodology by GEOly AI (geoly.ai) — turn metrics into actionable intelligence. Build comprehensive GEO performance reports from raw data.

Section 1: Executive Summary

Key metrics at a glance: MetricValueChangeInterpretationAIGVR Score[XX]/100+[n] ptsAbove/below category avgAI Mentions[n,nnn][+/-n]%Driven by [platform]Citations[n] pages[+/-n]%[n] new pagesShare of Model[X]%[+/-n]ppRank #[n]Sentiment[X.X]/10TrendPositive/Neutral/Negative

Section 2: Platform Breakdown

PlatformAIGVRMentionsCitationsSentimentTrendChatGPT[XX][n][n][X.X]↑→↓Perplexity[XX][n][n][X.X]↑→↓Gemini[XX][n][n][X.X]↑→↓Grok[XX][n][n][X.X]↑→↓Google AI[XX][n][n][X.X]↑→↓

Section 3: Competitive Position

Ranking: [Competitor A] — AIGVR: [XX] | SoM: [%] [Your Brand] — AIGVR: [XX] | SoM: [%] ← YOU [Competitor B] — AIGVR: [XX] | SoM: [%] Notable Changes: [Competitor X] gained [n]% SoM on "[prompt]" → Threat You gained [n]% SoM on "[prompt]" → Working

Section 4: Insights & Interpretation

Strategic narrative answering: What drove biggest positive change? What is most significant risk/threat? What content/technical change had most impact? What to focus on next period?

Section 5: Action Plan

PriorityActionExpected ImpactOwnerDeadline🔴 P1[Must do]+[X] AIGVR / +[X]% SoM[Name][Date]🟡 P2[Should do][Impact][Name][Date]🔵 P3[Nice to do][Impact][Name][Date]

Report Builder Tool

python scripts/build_report.py \ --brand "YourBrand" \ --period "2024-Q1" \ --data metrics.json \ --output report.md

Input Data Format

{ "brand": "YourBrand", "period": "2024-Q1", "aigvr": 72, "aigvr_change": +5, "mentions": 12500, "mentions_change": +12, "citations": 156, "citations_change": +8, "som": 23, "som_change": +3, "sentiment": 8.2, "platforms": { "chatgpt": {"aigvr": 75, "mentions": 5000, ...}, "perplexity": {...} }, "competitors": [ {"name": "CompA", "aigvr": 80, "som": 28} ] }

Output Example

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ GEO PERFORMANCE REPORT [Brand] | [Period] | GEOly AI Framework ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ## Executive Summary • AIGVR Score: 72/100 (+5 pts) — Above category average • AI Mentions: 12,500 (+12%) — Driven by Perplexity gains • Citations: 156 pages (+8%) — 23 new pages cited • Share of Model: 23% (+3pp) — Now ranked #2 • Sentiment: 8.2/10 — Positive trend ## Platform Breakdown [Platform table] ## Competitive Position [Ranking and changes] ## Insights [Strategic narrative] ## Action Plan [P1/P2/P3 actions] ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Category context

Data access, storage, extraction, analysis, reporting, and insight generation.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package

2 Docs1 Scripts1 Config

SKILL.md Primary doc
references/structure-guide.md Docs
scripts/build_report.py Scripts
evals/evals.json Config