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brand-copy

An AI agent skill from genspark-ai/genoffice, scored 61 out of 100 by code.

61/ 100C

Code score by group

  • Spec20/20
  • Description7/20
  • Procedure10/15
  • Done criteria0/15
  • Resources7/10
  • Scripts5/8
  • Safety7/7
  • Upkeep5/5

It loses the most points in Done criteria (15), the group that checks whether there is a checklist and a step that verifies the work.

What the author says it does

Turn product and audience information into multiple versions of taglines, selling points and brand story, delivered as Markdown

This is the description in the skill's own SKILL.md, written by its author, not by SkillCheatSheet.

Repository
genspark-ai/genoffice
Folder
skills/recommended/brand-copy
License
Apache-2.0
GitHub stars
12,211
SKILL.md lines
40
Other files
0

Add brand-copy to your agent

npx skills add genspark-ai/genoffice --skill brand-copy

The command uses the open skills CLI. A skill is instructions and scripts your agent will follow, so read it first: open the folder on GitHub at the commit that was scored.

More skills from genspark-ai/genoffice

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  2. business-report

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  3. executive-deck

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  4. job-description

    Turn a hiring need into a complete job description with responsibilities, requirements, nice-to-haves and a resume screening rubric, delivered as a Word document

    65C
  5. meeting-minutes

    Turn a transcript, chat log or loose notes into structured meeting minutes with decisions and action items, delivered as a Word document

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  6. nda-drafter

    Draft a one-way or mutual NDA from the cooperation background, with clause notes and risk points, not legal advice, delivered as a Word document

    65C
  7. kpi-dashboard

    Turn operating data into a KPI dashboard workbook with metric definitions, target vs actual, attainment rates and trend charts, delivered as an Excel workbook

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  8. deep-research

    Run multi-round searches with cross-checking and produce a research report with cited sources, delivered as a Word document

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All skills in genspark-ai/genoffice

Scores come from a snapshot of 300 public GitHub repositories taken on 12 November 2026. Every score is the result of fixed checks run by code; no AI is involved. How scoring works.