Ai Answer Gap

Organization

unifapi-agent

ai-answer-gap

When the user wants to find the prompts where their brand should be cited in AI answers but isn't — and who owns the answer instead — prioritized by AI search volume so content can attack the biggest gaps first. Also use on "AI answer gap," "AI content gap," "where am I missing from AI answers," "what prompts am I losing in AI," "GEO content gaps," "prompts I should own but don't," or "find my AI visibility gaps." For the full diagnostic audit, see ai-visibility-audit. For ongoing tracking, see llm-mention-tracking.

Overview

Publisher	unifapi-agent
Repository	`agents`
Skill name	`ai-answer-gap`
Stars	590
Forks	115
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by unifapi-agent on GitHub. Read the source before you install it.

Installation

Install the Ai Answer Gap AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/unifapi-agent/agents/tree/main/skills/ai-visibility-agent/ai-answer-gap
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/unifapi-agent/agents/tree/main/skills/ai-visibility-agent/ai-answer-gap

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/unifapi-agent/agents.git /tmp/agents
mkdir -p .claude/skills
cp -r /tmp/agents/skills/ai-visibility-agent/ai-answer-gap .claude/skills/ai-answer-gap

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ai Answer Gap in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ai Answer Gap on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ai Answer Gap is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

AI Answer Gap

Turn observed AI-answer gaps into a prioritized research and content backlog. Use an existing ai-visibility-audit or collect a dated panel first. Read available product context so proposed topics match what the product can credibly help with.

Use UnifAPI for live evidence

Connect with the unifapi skill to discover current schemas, prices and authentication before collecting data.

Workflow

Select relevant prompts. Group them by use case and search intent. /geo/keywords/search-volume supplies optional demand estimates; an absent estimate is unknown, not evidence that a useful niche prompt has no value.
Check current answers. Use /geo/answers for ChatGPT/Gemini, /geo/serp for Google AI Mode, and /seo/serp with include_ai_overview for Google Search AI Overviews. Keep engines, markets and natural/forced-search settings separate. Preserve exact answers and cited source URLs.
Describe the observed gap. Distinguish no answer, unsuccessful collection, brand absent from this answer, name-only mention, and cited brand. A sample is not proof of universal absence. Inspect references; top-level is_target and unused search results do not by themselves establish a citation.
Research sources. Open the actual cited pages. /geo/mentions/top-pages, /top-domains, and /search add separate indexed-corpus context. They do not supply the winning URL for a particular live prompt. /cross-aggregated-metrics gives group counts, not ownership of your prompt-panel gaps.
Propose a response. Identify the missing information, evidence or third-party representation. Choose an existing-page update, a new useful page, or an external research lead. Each proposed change needs a concrete source and a plausible benefit to readers. Name-only mentions and existing organic rankings are clues, not proof that formatting is the cause.
Prioritize. Consider product relevance, evidence of demand, gap quality, available expertise, and effort. Show the inputs and uncertainty. Optional scoring is a planning aid, not a predicted citation lift.
Validate later. Use the same panel and multiple dated runs after changes. Compare paired successful samples, show completion/answer rates, and avoid attributing every change to the edit.

Output

For each priority, give the exact prompt, engine/configuration, observed brand status, cited competitors or sources, suggested page/action, evidence, effort estimate and a validation plan. Preserve request ids and billed credits. An API failure should appear as missing evidence and never as a content gap.

See the audit methodology for coverage/share definitions, citation counting and evidence boundaries. Use llm-mention-tracking for budgeted snapshots and changes over time. This skill researches and drafts; it does not publish content or send outreach without authorization.

Frequently asked questions

What does the Ai Answer Gap AI skill do?

Why use Ai Answer Gap on TypingMind?

Because you install it once and use it with any model. Ai Answer Gap is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ai Answer Gap in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/unifapi-agent/agents/tree/main/skills/ai-visibility-agent/ai-answer-gap. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ai Answer Gap?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ai Answer Gap?

As many as you like. As long as a model supports skills, you can use Ai Answer Gap with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ai Answer Gap AI skill free?

Yes. It is published on GitHub by unifapi-agent under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Creative Ideation

NousResearch

OrganizationPopular

Generate ideas via named methods from creative practice.

Inference Sh Cli

Run 150+ AI apps (image, video, LLM) via inference.sh CLI.

Firecrawl Build Search

firecrawl

OrganizationPopular

Integrate Firecrawl `/search` into product code and agent workflows. Use when an app needs discovery before extraction, when the feature starts with a query instead of a URL, or when the system should…

Firecrawl Build

Integrate Firecrawl into application code whenever a product, agent, or workflow needs web data inside the app — web search, live search results, page scraping, structured extraction, or browser…

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

AI Answer Gap

Use UnifAPI for live evidence

Workflow

Output

Frequently asked questions

Related AI Skills

Set up your own AI workspace now