aeo-analytics-free
Track AI visibility — measure whether a brand is mentioned and cited by AI assistants (Gemini, ChatGPT, Perplexity) for target prompts. Runs scans, tracks mention/citation rates over time, detects trends, and identifies opportunities. Uses Gemini API free tier (with grounding) as primary method, web search as fallback. Use when a user wants to: check if AI models mention their brand, track AI citation changes over time, measure AEO content effectiveness, monitor competitor AI visibility, or audit their brand's presence in AI-generated answers. Pairs with aeo-prompt-research-free (identifies prompts) and aeo-content-free (creates/refreshes content). This skill closes the loop by measuring results.
安装 / 下载方式
TotalClaw CLI推荐
totalclaw install clawskills:clawskills~psyduckler-aeo-analytics-freecURL直接下载,无需登录
curl -fsSL https://skills.taituai.com/api/skills/clawskills%3Aclawskills~psyduckler-aeo-analytics-free/file -o psyduckler-aeo-analytics-free.md# AEO Analytics (Free) > **Source:** [github.com/psyduckler/aeo-skills](https://github.com/psyduckler/aeo-skills/tree/main/aeo-analytics-free) > **Part of:** [AEO Skills Suite](https://github.com/psyduckler/aeo-skills) — [Prompt Research](https://github.com/psyduckler/aeo-skills/tree/main/aeo-prompt-research-free) → [Content](https://github.com/psyduckler/aeo-skills/tree/main/aeo-content-free) → Analytics Track whether AI assistants mention and cite your brand — and how that changes over time. ## Requirements - **Primary:** Gemini API key (free from aistudio.google.com) — enables grounding with source data - **Fallback:** `web_search` only — weaker signal but zero API keys needed - `web_fetch` — optional, for deeper analysis of cited pages ## Input - **Domain** (required) — the brand's website (e.g., `tabiji.ai`) - **Brand names** (required) — names to search for in responses (e.g., `["tabiji", "tabiji.ai"]`) - **Prompts** (required for first scan) — list of target prompts to track. Can come from `aeo-prompt-research-free` output. - **Data file path** (optional) — where to store scan history. Default: `aeo-analytics/<domain>.json` ## Commands The skill supports three commands: ### `scan` — Run a new visibility scan Execute all tracked prompts against the AI model and record results. ### `report` — Generate a visibility report Analyze accumulated scan data and produce a formatted report. ### `add-prompts` / `remove-prompts` — Manage tracked prompts Add or remove prompts from the tracking list. --- ## Scan Workflow ### Step 1: Load or Initialize Data Check if a data file exists for this domain. If yes, load it. If no, create a new one. See `references/data-schema.md` for the full JSON schema. ### Step 2: Run Prompts For each tracked prompt: **Method A — Gemini API with grounding (preferred):** See `references/gemini-grounding.md` for API details. 1. Send prompt to Gemini API with `googleSearch` tool enabled 2. From the response, extract: - **Response text** — the AI's answer - **Grounding chunks** — the web sources cited (URLs + titles) - **Web search queries** — what the AI searched for 3. Analyze the response: - **Mentioned?** — Search response text for brand names (case-insensitive, word-boundary match) - **Mention excerpt** — Extract the sentence(s) containing the brand name - **Cited?** — Check if brand's domain appears in any grounding chunk URI - **Cited URLs** — List the specific brand URLs cited - **Sentiment** — Classify the mention context as positive/neutral/negative - **Competitors** — Extract other brand names and domains from response + citations **Method B — Web search fallback (if no Gemini API key):** 1. `web_search` the exact prompt text 2. Check if brand's domain appears in search results 3. Record as "web-proxy" method (less direct than grounding) ### Step 3: Save Results Append the scan results to the data file. Never overwrite previous scans — history is the whole point. ### Step 4: Quick Summary After scanning, output a brief summary: - Prompts scanned - Current mention rate and citation rate - Change vs. last scan (if applicable) - Any notable changes (new mentions, lost citations) --- ## Report Workflow ### Per-Prompt Detail For each tracked prompt, show: ``` 1. "[prompt text]" Scans: [total] (since [first scan date]) Mentioned: [count]/[total] ([%]) — [trend arrow] [trend description] Cited: [count]/[total] ([%]) Latest: [✅/❌ Mentioned] + [✅/❌ Cited] Sentiment: [positive/neutral/negative] Competitors mentioned: [list] ``` If mentioned in latest scan, include the mention excerpt. If not mentioned, note which sources were cited instead and rate the opportunity (HIGH/MEDIUM/LOW). ### Summary Section ``` VISIBILITY SCORE Brand mentioned: [X]/[total] prompts ([%]) in latest scan Brand cited: [X]/[total] prompts ([%]) in latest scan TRENDS (last [N] days, [N] scans) Mention rate: [%] → [trend] Citation rate: [%] → [trend] Most improved: [prompt] ([old rate] → [new rate]) Most volatile: [prompt] (mentioned [X]/[N] scans) Consistently absent: [list of prompts never mentioned] COMPETITOR SHARE OF VOICE [Competitor 1] — mentioned in [X]/[total] prompts [Competitor 2] — mentioned in [X]/[total] prompts [Brand] — mentioned in [X]/[total] prompts NEXT ACTIONS → [Prioritized recommendations based on gaps and trends] ``` ### Recommendations Logic - **High opportunity:** Prompt has 0% mention rate + no strong owner in citations → create content - **Close to winning:** Prompt has mentions but no citations → refresh content for citation-worthiness - **Volatile:** Mention rate between 20-60% → content exists but needs strengthening - **Won:** Mention rate >80% + citation rate >50% → maintain, monitor for decay --- ## Data Management - Data file location: `aeo-analytics/<domain>.json` - Schema: see `references/data-schema.md` - Each scan appends to the `scans` array — never delete history - Prompts can be added/removed without affecting historical data - When adding new prompts, they start with 0 scans (no backfill) ## Tips - Run scans at consistent intervals (weekly or biweekly) for meaningful trend data - After publishing new AEO content, wait 2-4 weeks for indexing before expecting changes - Gemini's grounding results can vary run-to-run — that's normal. Aggregate data over multiple scans is more reliable than any single result - Track 10-20 prompts max for a focused view. Too many dilutes the signal - This skill completes the AEO loop: Research (aeo-prompt-research-free) → Create/Refresh (aeo-content-free) → Measure (this skill) → repeat