Skill audit report
Generate a portfolio-level dashboard across ALL client brands — per-client RAG health scores, campaign activity, budget pacing, aggregate KPIs, team utilization, pending approvals, upcoming deadlines, and an alerts panel — built for agency standups and weekly reviews. Triggers on \"/digital-marketing-pro:agency-dashboard\", \"how are all our clients doing\", \"portfolio health check\", \"budget pacing across accounts\", \"which accounts are at risk\". Enumerates every brand under ~/.claude-marketing/brands/ and pulls data via campaign-tracker.py, execution-tracker.py, and team-manager.py; drill into a single client with /digital-marketing-pro:performance-report or /digital-marketing-pro:client-report.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO76
787 GitHub stars
Stars/forks activity
INFO71
787 stars, 132 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
21d since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
WARN54
command execution surface, credential or environment access
Install availability
PASS92
npx skills add indranilbanerjee/digital-marketing-pro --skill agency-dashboard
Install command safety
PASS92
standard package or runtime install path
Permission surface
WARN50
secrets or environment access, shell or command execution
Repository evidence
PASS86
https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/agency-dashboard
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 agency-dashboard
Repository
88
https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/agency-dashboard
License
86
MIT
Maintenance
100
21d 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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Usable description available
Dependency risk
54
command execution surface, credential or environment access
Install command safety
92
standard package or runtime install path
Permission surface
50
secrets or environment access, shell or command execution
Stars/forks activity
71
787 stars, 132 forks; issue activity unavailable in current metadata
Adoption
88
787 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
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
Shell or command execution
highSkill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
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.
Secrets or environment access
highSkill metadata references credentials, tokens, environment variables, or secret-bearing workflows.