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ai-search-guruai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool/skills/gaps/SKILL.md

gaps

Skill432 starsChanged 11 days agoMITView on GitHub

Finds prompts and segments where no brand leads yet, and suggests what to do.

5 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

3 rules. 0 are common, 3 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 4 edited versions we read keep these.

  • 3

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Don't call a prompt won or lost from one answer: look across its answers and engines.

    line 42
  2. Distinctive:

    Never make up a volume: write "unknown" where none is known.

    line 43
  3. Distinctive:

    Never promise the brand will lead after an action.

    line 44

“Common” is measured: kept by at least 6 in 10 of the 4 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

No clear leader

The prompts, topics and segments where AI engines don't recommend one brand most of the time: open ground the brand can take first.

When to use

  • "Which use cases have no clear winner yet?", "Where is nobody leading?", "Unmet needs."
  • To work on one prompt a competitor already wins, the Beat a competitor skill fits better.

What to read

  1. list_topics and list_prompts: the brand's topics and tracked prompts.
  2. get_prompt_performance: the brand's place on each prompt, per engine.
  3. list_ai_answers for the prompts: which brands each engine recommends.
  4. get_competitor_comparison: where competitors lead, to tell an open prompt from a taken one.
  5. get_prompt_volumes: how often each prompt is searched, where known.

Steps

  1. For each prompt, count which brands the engines recommend across its answers.
  2. A prompt has no clear leader when no brand is recommended in most of its answers. Group these prompts by topic or segment.
  3. Order them by searches a month where known, then by how close the brand already is.
  4. For each, suggest one action: a page to write or update, a question to answer, a source to be listed on.
  5. Offer to add the top ones to Action Center with create_action; the app asks the person first.

Output

  1. A table: Prompt or segment, Engines, Brands that appear, The brand's place, Searches a month, Suggested action.
  2. The three to start with, and why.

Don't

  • Don't call a prompt won or lost from one answer: look across its answers and engines.
  • Never make up a volume: write "unknown" where none is known.
  • Never promise the brand will lead after an action.

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Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.