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ansvisoransvisor/ansvisor/skills/analyze/SKILL.md

analyze

Skill233 starsChanged 5 months agoMITView on GitHub

Explains what changed and why, and whether it beats the normal week-to-week swing.

70 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use constitution, revise and 7 more.

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Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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The file

We split this skill into the rules it gives an agent

6 rules. 0 are common, 5 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 59 edited versions we read keep these.

  • 5

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Read one to three of these, the ones the request is about, for the chat's brand:

    line 17
  2. Very specific:

    Use list_brands only when no brand is selected, and open_page to link the page that shows the numbers.

    line 27
  3. Distinctive:

    Ask for the period or the competitor only when the request names neither and the answer would change with it.

    line 33
  4. Distinctive:

    Read the period and the one before it, for the sources the request is about.

    line 37
  5. Distinctive:

    Never present a cut list as complete, or a change within normal swing as a trend.

    line 52
  6. Distinctive:

    Never report a platform the plan doesn't track.

    line 53

“Common” is measured: kept by at least 6 in 10 of the 59 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

Analyze

The playbook of the /analyze shortcut ("Analyze …"): what changed in the brand's AI visibility, why, and whether it is more than normal swing.

Data plan

Read one to three of these, the ones the request is about, for the chat's brand:

  1. Visibility: get_overview_summary, or get_visibility_summary and get_visibility_trend.
  2. Prompts: get_prompt_performance and list_prompts.
  3. Mentions: get_mentions_summary, and get_mentions_perception for how AI describes the brand.
  4. Competitors: get_competitor_comparison.
  5. Citations: list_citations.
  6. AI traffic: get_ai_traffic_summary, and get_gsc_summary or get_ga_summary when connected.
  7. Why one number moved: explain_change.

Use list_brands only when no brand is selected, and open_page to link the page that shows the numbers.

Scope: the page's date range when the message came with one, else the last 30 days against the 30 before, on every platform the plan tracks. Give dates only for the period before, or a period the person names.

Questions

  • Ask for the period or the competitor only when the request names neither and the answer would change with it. Otherwise use the default scope and say so.

Steps

  1. Read the period and the one before it, for the sources the request is about.
  2. Lead with the change: the metric, both values, and whether it is within normal swing.
  3. Then why: the prompts, platforms, pages and competitors that moved most, with their numbers.
  4. Say what moved together and when; never that one change caused another.

Output

Text, with a table when it compares more than three rows: Metric or prompt, This period, Before, Change.

Next moves

Two or three, such as "Send to Action Center" for a finding worth acting on, or refreshing a page that lost citations.

Don't

  • Never present a cut list as complete, or a change within normal swing as a trend.
  • Never report a platform the plan doesn't track.

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