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Documentation Index

Fetch the complete documentation index at: https://docs.peec.ai/llms.txt

Use this file to discover all available pages before exploring further.

Start by asking your AI assistant to list your projects, then pick one:
“List my Peec AI projects”
Include a time range in your questions. “Last 30 days”, “this month”, or “past week” gets you better results.
For the most common workflows (weekly pulse, competitor radar, engine scorecard, source audit, campaign tracker), use a built-in prompt instead. One slash command runs the full analysis and formats the output.

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Example workflows

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1. Brand visibility overview

“How visible is my brand across AI search engines this month?”
Returns your visibility percentage, sentiment score, share of voice, and average position across all tracked AI models.

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2. Competitive benchmarking by AI model

“Compare our visibility against competitors, broken down by AI model”
Table showing each brand’s visibility across ChatGPT, Perplexity, Gemini, and other platforms. See where you lead and where competitors outperform you.

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3. Source citation analysis

“Which of our pages get cited most by AI engines?”
Ranked list of your URLs with citation counts, retrieval numbers, and page types.

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4. Topic deep-dive

“How do we perform on the topic ‘sustainable fashion’ vs competitors?”
Brand-by-brand comparison within a specific topic: visibility, share of voice, and sentiment.

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5. Visibility trend

“Show me our visibility trend over the last 30 days”
Daily visibility data with notable changes highlighted.

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More ideas

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Brand visibility

“Break down our brand visibility by AI model for the past two weeks.”
Get an overview of your performance for each AI model.
“Which topics have the highest and lowest visibility for our brand?”
Identify the strengths and weaknesses in your AI search presence.

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Competitive analysis

“Compare our share of voice against all competitors for the last month.”
Your mention share vs the competitive set.
“How does our sentiment compare to [competitor name] on ChatGPT?”
Find out how positively AI models describe you vs a specific competitor.
“Which competitor is mentioned first most often across all AI models?”
Understand who consistently wins the top position in AI responses.

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Sources and citations

“What are the most cited domains in AI responses for our prompts?”
Use this to understand which websites have the most authority in your space.
“How often is our website retrieved and cited? Break it down by AI model.”
You can make these kinds of queries to gain an idea of how your domain’s source authority is across AI platforms.
“Which competitor domains have the highest citation rate?”
Find out which competitor websites AI treats as authoritative.
“Pull the content of the top-cited competitor URL on the topic ‘project management tools’ and tell me what it covers that our own page doesn’t.”
The MCP fetches the scraped markdown of the source Peec has indexed, so your AI assistant can compare structure, depth, and framing against your own content.

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Reporting

“Give me a weekly summary: our visibility, share of voice, and sentiment for the past 7 days vs the previous 7 days.”
A quick health check you can run every week.
“Break down our visibility by country for the last month.”
Understand the geographic differences in your AI search presence if you have prompts in multiple markets.
“Which topics have high competitor visibility but low visibility for our brand?”
Find opportunities where competitors are visible, but you’re not.

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Actions and next steps

“What should we focus on next quarter to improve AI visibility?”
Returns Peec’s opportunity-scored recommendations grouped by owned pages, editorial coverage, reference sites, and UGC communities. No invented advice. Rankings are computed from your actual visibility gaps.
“Our biggest opportunity is UGC on YouTube. What specifically should we do there?”
The MCP first calls the actions overview to surface the opportunity, then drills into the UGC domain with concrete outreach suggestions (creators to contact, formats that work).

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Edit your project setup

“Add this prompt to my project: ‘best CRM for remote sales teams 2026’. Target US, tag it ‘competitive’.”
The assistant resolves the tag and the project, then confirms with you before calling create_prompt.
“Create a topic called ‘Pricing’ and move every prompt that mentions ‘cost’ or ‘pricing’ into it.”
The assistant lists matching prompts first, creates the topic, and calls update_prompt for each one. Only after you confirm the list.
“Start tracking Acme as a competitor. Their domains are acme.com and getacme.io, and they also go by ‘Acme Labs’.”
The assistant calls create_brand with the domains and aliases you provided.
“List my tags, tell me which ones are attached to fewer than 3 prompts, and delete those after I confirm.”
The assistant uses list_tags and list_prompts, surfaces the low-use tags, and only calls delete_tag for the ones you approve.
“Here are 30 prompts from our customer-research doc. Add them to my project under the ‘Discovery’ topic, all targeting the US.”
The assistant resolves the topic ID once, then calls create_prompts with all 30 entries in a single batch. Duplicates and any IDs that don’t resolve come back per-item so nothing silently fails.
“Read my current brand profile, change the industry to ‘B2B SaaS’, and add ‘AI search analytics’ to our product list.”
The assistant calls get_project_profile, shows you the current values, merges your changes, and calls set_project_profile after you confirm. Saving triggers a refresh of the AI-generated prompt suggestions.

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Workflows validated in the MCP Challenge

“After our pricing change last week, find every URL AI models are citing for pricing-related prompts that still mentions the old price. Draft personalized outreach emails to each publication.”
The MCP pulls get_url_report and get_domain_report for pricing topics, uses get_url_content to inspect which pages still reference the old price, and drafts outreach. Works for any stale information (pricing, product names, feature lists). Add a Gmail or Firecrawl MCP to the session to send the outreach in the same flow.
“For our owned domain, show URLs whose retrieval rate dropped most over the last 90 days compared to the prior 90. Rank them by the size of the drop. These are our content-refresh priorities.”
Pulls get_url_report with date dimension filtered to your domain, computes rolling-window deltas, and surfaces URLs where AI engines are citing you less over time. Content refresh is a high-leverage GEO action. Phrase the query to explicitly compare time windows. Vague queries like “which content needs a refresh?” tend to return a generic gap analysis instead of a time-decay ranking.
“For every prompt we track, compare our visibility to [Competitor] and rank the prompts where they beat us most.”
get_brand_report dimensioned by prompt_id for both brands returns a ranked gap table. Output: the exact queries where the competitor is mentioned and you are not. Use list_prompts to resolve prompt_id values to the actual prompt text for the final ranking.
“Which URLs are AI models citing most when they describe us negatively?”
The MCP pulls get_url_report for top-retrieved pages, cross-references with per-chat sentiment via list_chats + get_chat, and surfaces the specific URLs dragging the score down. Often: an old review, a negative forum thread, or a competitor comparison page.

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Tips

To make the experience smoother or complete, take a look at the following tips:
  • Include dates: Always specify a time range (e.g. “Last 7 days”, “Last month”).
  • Name brands: Mention specific competitors by name (e.g. “How do I compare against [competitor]?”).
  • Ask for breakdowns: “Break down by model” or “split by topic” gives per-dimension results.
  • Start broad, then drill down: Start with your overview, then follow up on what stands out.