Skill audit report
Audience research module — builds six-dimension buyer personas (demographic, psychographic, behavioral, need-state, information, decision), Jobs-to-Be-Done maps, RFM/behavioral/lifecycle segmentation models, anti-personas with exclusion criteria, B2B buying-committee maps, and lookalike seed specs. Triggers on \"/digital-marketing-pro:audience-intelligence\", \"who are our customers\", \"build buyer personas\", \"segment our audience\", \"run a JTBD analysis\". Reads the brand profile, industry benchmarks, and campaign history, and works from CRM/survey/analytics data when supplied — or labels hypothesis personas explicitly when data is thin. For a single quick persona document, /digital-marketing-pro:audience-profile is the lighter sibling.
Skill audit report
Audience research module — builds six-dimension buyer personas (demographic, psychographic, behavioral, need-state, information, decision), Jobs-to-Be-Done maps, RFM/behavioral/lifecycle segmentation models, anti-personas with exclusion criteria, B2B buying-committee maps, and lookalike seed specs. Triggers on \"/digital-marketing-pro:audience-intelligence\", \"who are our customers\", \"build buyer personas\", \"segment our audience\", \"run a JTBD analysis\". Reads the brand profile, industry benchmarks, and campaign history, and works from CRM/survey/analytics data when supplied — or labels hypothesis personas explicitly when data is thin. For a single quick persona document, /digital-marketing-pro:audience-profile is the lighter sibling.
Skill audit report
Audience research module — builds six-dimension buyer personas (demographic, psychographic, behavioral, need-state, information, decision), Jobs-to-Be-Done maps, RFM/behavioral/lifecycle segmentation models, anti-personas with exclusion criteria, B2B buying-committee maps, and lookalike seed specs. Triggers on \"/digital-marketing-pro:audience-intelligence\", \"who are our customers\", \"build buyer personas\", \"segment our audience\", \"run a JTBD analysis\". Reads the brand profile, industry benchmarks, and campaign history, and works from CRM/survey/analytics data when supplied — or labels hypothesis personas explicitly when data is thin. For a single quick persona document, /digital-marketing-pro:audience-profile is the lighter sibling.
Skill audit report
Audience research module — builds six-dimension buyer personas (demographic, psychographic, behavioral, need-state, information, decision), Jobs-to-Be-Done maps, RFM/behavioral/lifecycle segmentation models, anti-personas with exclusion criteria, B2B buying-committee maps, and lookalike seed specs. Triggers on \"/digital-marketing-pro:audience-intelligence\", \"who are our customers\", \"build buyer personas\", \"segment our audience\", \"run a JTBD analysis\". Reads the brand profile, industry benchmarks, and campaign history, and works from CRM/survey/analytics data when supplied — or labels hypothesis personas explicitly when data is thin. For a single quick persona document, /digital-marketing-pro:audience-profile is the lighter sibling.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO76
792 GitHub stars
Stars/forks activity
INFO71
792 stars, 132 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
19d since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
PASS90
no major dependency risk hints in public metadata
Install availability
PASS92
npx skills add indranilbanerjee/digital-marketing-pro --skill audience-intelligence
Install command safety
PASS92
standard package or runtime install path
Permission surface
PASS86
filesystem or document access
Repository evidence
PASS86
https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add indranilbanerjee/digital-marketing-pro --skill audience-intelligence
Repository
88
https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence
License
86
MIT
Maintenance
100
19d since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
86
Warnings
Method
This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.
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OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO76
792 GitHub stars
Stars/forks activity
INFO71
792 stars, 132 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
19d since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
PASS90
no major dependency risk hints in public metadata
Install availability
PASS92
npx skills add indranilbanerjee/digital-marketing-pro --skill audience-intelligence
Install command safety
PASS92
standard package or runtime install path
Permission surface
PASS86
filesystem or document access
Repository evidence
PASS86
https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add indranilbanerjee/digital-marketing-pro --skill audience-intelligence
Repository
88
https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence
License
86
MIT
Maintenance
100
19d since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
86
Warnings
Method
This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.
Compare nearby options
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
1.9K Stars · Audit report
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
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OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO76
792 GitHub stars
Stars/forks activity
INFO71
792 stars, 132 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
19d since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
PASS90
no major dependency risk hints in public metadata
Install availability
PASS92
npx skills add indranilbanerjee/digital-marketing-pro --skill audience-intelligence
Install command safety
PASS92
standard package or runtime install path
Permission surface
PASS86
filesystem or document access
Repository evidence
PASS86
https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add indranilbanerjee/digital-marketing-pro --skill audience-intelligence
Repository
88
https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence
License
86
MIT
Maintenance
100
19d since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
86
Warnings
Method
This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.
Compare nearby options
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
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OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO76
792 GitHub stars
Stars/forks activity
INFO71
792 stars, 132 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
19d since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
PASS90
no major dependency risk hints in public metadata
Install availability
PASS92
npx skills add indranilbanerjee/digital-marketing-pro --skill audience-intelligence
Install command safety
PASS92
standard package or runtime install path
Permission surface
PASS86
filesystem or document access
Repository evidence
PASS86
https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add indranilbanerjee/digital-marketing-pro --skill audience-intelligence
Repository
88
https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence
License
86
MIT
Maintenance
100
19d since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
86
Warnings
Method
This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.
Compare nearby options
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
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Usable description available
Dependency risk
90
no major dependency risk hints in public metadata
Install command safety
92
standard package or runtime install path
Permission surface
86
filesystem or document access
Stars/forks activity
71
792 stars, 132 forks; issue activity unavailable in current metadata
Adoption
88
792 GitHub stars
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
Network access
mediumSkill likely fetches remote pages, APIs, repositories, or external services.
Filesystem access
mediumSkill may read or write project files, documents, generated artifacts, or local workspace state.
Usable description available
Dependency risk
90
no major dependency risk hints in public metadata
Install command safety
92
standard package or runtime install path
Permission surface
86
filesystem or document access
Stars/forks activity
71
792 stars, 132 forks; issue activity unavailable in current metadata
Adoption
88
792 GitHub stars
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
Network access
mediumSkill likely fetches remote pages, APIs, repositories, or external services.
Filesystem access
mediumSkill may read or write project files, documents, generated artifacts, or local workspace state.
Usable description available
Dependency risk
90
no major dependency risk hints in public metadata
Install command safety
92
standard package or runtime install path
Permission surface
86
filesystem or document access
Stars/forks activity
71
792 stars, 132 forks; issue activity unavailable in current metadata
Adoption
88
792 GitHub stars
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
Network access
mediumSkill likely fetches remote pages, APIs, repositories, or external services.
Filesystem access
mediumSkill may read or write project files, documents, generated artifacts, or local workspace state.
Usable description available
Dependency risk
90
no major dependency risk hints in public metadata
Install command safety
92
standard package or runtime install path
Permission surface
86
filesystem or document access
Stars/forks activity
71
792 stars, 132 forks; issue activity unavailable in current metadata
Adoption
88
792 GitHub stars
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
Network access
mediumSkill likely fetches remote pages, APIs, repositories, or external services.
Filesystem access
mediumSkill may read or write project files, documents, generated artifacts, or local workspace state.