{"query":"audience-intelligence","filters":{"category":null,"platform":null,"track":null,"safety":null,"include_blocked":false,"min_stars":0},"total":1,"skills":[{"rank":1,"match_type":"exact","match_score":99,"raw_match_score":835.4,"semantic_relevance":100,"ranking_signals":{"retrieval":810,"semantic":100,"quality":10.9,"projectPopularity":14.5,"verifiedOutcomes":0,"verifiedSource":0},"slug":"indranilbanerjee-audience-intelligence","name":"audience-intelligence","description":"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.","tagline":"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 lo","category":"research","tags":["agent-skill"],"author":{"name":"indranilbanerjee","verified":false,"url":"https://github.com/indranilbanerjee"},"attribution":{"status":"registry_indexed","statusLabel":"Registry indexed","shortLabel":"REGISTRY INDEXED","sourceLabel":"github candidate review","sourceDetail":"indranilbanerjee/digital-marketing-pro","creatorName":"indranilbanerjee","creatorUrl":"https://github.com/indranilbanerjee","sourceUrl":"https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence","indexedBy":"OpenAgentSkill community index","claimUrl":"https://www.openagentskill.com/skills/indranilbanerjee-audience-intelligence#claim-this-skill","claimCta":"Claim this skill","trustNote":"This listing was indexed from public sources and is not marked official until a maintainer claim is approved.","publicNote":"Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals."},"stats":{"stars":792,"forks":132,"verified_installs":0,"install_attempts":0,"successful_runs":0,"total_outcomes":0,"downloads":0,"rating":0,"review_count":0,"quality_score":43.69},"quality":{"score":76,"tier":"strong","label":"Strong","summary":"Solid option that is likely worth shortlisting for production workflows.","signals":[{"label":"GitHub stars","value":"792","tone":"positive"},{"label":"Freshness","value":"19d ago","tone":"positive"},{"label":"Install ready","value":"Yes","tone":"positive"},{"label":"License","value":"MIT","tone":"neutral"}],"warnings":[]},"trust":{"version":"trust-score-v4","score":80,"tier":"strong","label":"Strong shortlist","summary":"Good trust signals with a few areas worth checking before rollout.","recommendedAction":"Test in a sandbox workflow and compare its install path with close alternatives.","dimensions":[{"id":"github_adoption","label":"GitHub 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metadata"},{"status":"pass","label":"Recent maintenance","detail":"19d since push"},{"status":"pass","label":"License clarity","detail":"MIT"},{"status":"warn","label":"README/SKILL.md completeness","detail":"Public metadata needs stronger README/SKILL.md context"},{"status":"pass","label":"Dependency/runtime risk","detail":"no major dependency risk hints in public metadata"},{"status":"pass","label":"Install availability","detail":"npx skills add indranilbanerjee/digital-marketing-pro --skill audience-intelligence"},{"status":"pass","label":"Install command safety","detail":"standard package or runtime install path"},{"status":"pass","label":"Permission surface","detail":"filesystem or document access"},{"status":"pass","label":"Repository evidence","detail":"https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence"},{"status":"pass","label":"Review status","detail":"AI review data available"},{"status":"info","label":"Agent Proven 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state.","severity":"medium"}],"policy_warnings":["Quality score needs review"],"constraints_applied":{"max_risk":"medium","needs_install_command":true,"min_stars":0}},"safety_gate":{"tier":"reviewed","label":"Reviewed","badge":"REVIEWED","auto_install_policy":"review","auto_install_allowed":false,"human_review_required":true,"blocked":false,"recommended_action":"Review the audit page, then allow agent install in a sandboxed workflow.","reasons":["Safe-to-try audit","68/100 agent safety score"]},"supply_profile":{"track":{"slug":"research","label":"Research and knowledge work","shortLabel":"Research","description":"Deep research, source comparison, literature review, RAG, knowledge search, and reports."},"scenario":{"label":"Research agents","description":"I need my agent to research a topic, compare sources, and produce a concise report.","useCases":[{"slug":"research-agents","title":"Research agents"},{"slug":"marketing-growth","title":"Marketing and 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context"]},"decision":{"readiness_score":87,"readiness_label":"Production-ready","headline":"Primary pick for Research agents","role":"Primary pick","primary_fit":"Research agents","best_for":["Research agents workflows","Claude Code teams","teams that value GitHub adoption signals"],"risks":["No OpenAgentSkill engagement data yet"],"next_steps":["Install it in a sandbox agent and run one Research agents task end to end.","Compare output quality, latency, and failure behavior against at least one alternative.","Promote it into production only after reviewing repository permissions, license, and maintenance signals."]},"agent_readable_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"indranilbanerjee-audience-intelligence","name":"audience-intelligence","description":"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.","category":"research","url":"https://www.openagentskill.com/skills/indranilbanerjee-audience-intelligence","repository":"https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence","github_repo":"indranilbanerjee/digital-marketing-pro"},"suited_tasks":["Research agents workflows","Claude Code teams","teams that value GitHub adoption signals","Search sources","Extract claims","Synthesize findings","Collect channel signals","Prioritize opportunities"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add indranilbanerjee/digital-marketing-pro --skill audience-intelligence","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add indranilbanerjee-audience-intelligence"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"audience-intelligence\" agent skill from https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: 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. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"indranilbanerjee-audience-intelligence\",\"task\":\"Install audience-intelligence\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"audience-intelligence\" as a Claude Code skill from https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: 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. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"indranilbanerjee-audience-intelligence\",\"task\":\"Install audience-intelligence\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"audience-intelligence\" from https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: 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. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"indranilbanerjee-audience-intelligence\",\"task\":\"Install audience-intelligence\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."}],"handoff_url":"https://www.openagentskill.com/api/skills/indranilbanerjee-audience-intelligence/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/indranilbanerjee-audience-intelligence"},"trust":{"score":80,"label":"Strong shortlist","version":"trust-score-v4","install_policy":"human_review_before_install","evidence":{"stars":"792 GitHub stars","repoActivity":"792 stars, 132 forks","lastPushed":"19d since push","license":"MIT","repository":"https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence","install":"npx skills add indranilbanerjee/digital-marketing-pro --skill audience-intelligence","installSafety":"standard package or runtime install path","permissionSurface":"filesystem or document access","documentation":"Thin public metadata","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":false,"sandbox_required":true,"reason":"Human review or sandbox validation is required before automatic installation."},"best_for":["research","agent-skill"],"known_risks":["Quality score needs review","README/SKILL.md completeness: Public metadata needs stronger README/SKILL.md context"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":84,"risk_level":"safe_to_try","risk_label":"Safe to try","warnings":["Quality score needs review","README/SKILL.md completeness: Public metadata needs stronger README/SKILL.md context"]},"safety_gate":{"tier":"reviewed","label":"Reviewed","auto_install_policy":"review","auto_install_allowed":false,"human_review_required":true,"blocked":false,"recommended_action":"Review the audit page, then allow agent install in a sandboxed workflow."},"quality":{"score":76,"label":"Strong"},"supply":{"track":"Research and knowledge work","scenario":"Research agents","maintenance":"19d since push","risk":"Safe to try"},"alternative_skills":[],"do_not_use_when":["teams that need a vendor-supported SLA","high-compliance environments without internal security review","No OpenAgentSkill engagement data yet","Quality score needs review","README/SKILL.md completeness: Public metadata needs stronger README/SKILL.md context","Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface","Automatic installation in a production workspace"],"agent_contract":{"task_input":"Use audience-intelligence in an agent workflow","recommended_action":"Review the audit page, then allow agent install in a sandboxed workflow.","install_policy":"review","minimum_review_before_use":["Trust: 80/100 Strong shortlist","Audit: 84/100 Safe to try","Safety: 68/100 Review before install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"indranilbanerjee-audience-intelligence (audience-intelligence)","install_command":"npx skills add indranilbanerjee/digital-marketing-pro --skill audience-intelligence","risk_summary":"Safe to try; Reviewed; Review before production","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"indranilbanerjee-audience-intelligence","task":"Use audience-intelligence in an agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/indranilbanerjee-audience-intelligence","api":"https://www.openagentskill.com/api/agent/skills/indranilbanerjee-audience-intelligence","audit":"https://www.openagentskill.com/skills/indranilbanerjee-audience-intelligence/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=indranilbanerjee-audience-intelligence&task=Use%20audience-intelligence%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20audience-intelligence%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20audience-intelligence%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/indranilbanerjee-audience-intelligence/install","manifest":"https://www.openagentskill.com/api/registry/manifest/indranilbanerjee-audience-intelligence"}},"machine_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"indranilbanerjee-audience-intelligence","name":"audience-intelligence","description":"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.","category":"research","url":"https://www.openagentskill.com/skills/indranilbanerjee-audience-intelligence","repository":"https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence","github_repo":"indranilbanerjee/digital-marketing-pro"},"suited_tasks":["Research agents workflows","Claude Code teams","teams that value GitHub adoption signals","Search sources","Extract claims","Synthesize findings","Collect channel signals","Prioritize opportunities"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add indranilbanerjee/digital-marketing-pro --skill audience-intelligence","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add indranilbanerjee-audience-intelligence"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"audience-intelligence\" agent skill from https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: 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. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"indranilbanerjee-audience-intelligence\",\"task\":\"Install audience-intelligence\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"audience-intelligence\" as a Claude Code skill from https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: 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. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"indranilbanerjee-audience-intelligence\",\"task\":\"Install audience-intelligence\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"audience-intelligence\" from https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: 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. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"indranilbanerjee-audience-intelligence\",\"task\":\"Install audience-intelligence\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."}],"handoff_url":"https://www.openagentskill.com/api/skills/indranilbanerjee-audience-intelligence/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/indranilbanerjee-audience-intelligence"},"trust":{"score":80,"label":"Strong shortlist","version":"trust-score-v4","install_policy":"human_review_before_install","evidence":{"stars":"792 GitHub stars","repoActivity":"792 stars, 132 forks","lastPushed":"19d since push","license":"MIT","repository":"https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence","install":"npx skills add indranilbanerjee/digital-marketing-pro --skill audience-intelligence","installSafety":"standard package or runtime install path","permissionSurface":"filesystem or document access","documentation":"Thin public metadata","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":false,"sandbox_required":true,"reason":"Human review or sandbox validation is required before automatic installation."},"best_for":["research","agent-skill"],"known_risks":["Quality score needs review","README/SKILL.md completeness: Public metadata needs stronger README/SKILL.md context"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":84,"risk_level":"safe_to_try","risk_label":"Safe to try","warnings":["Quality score needs review","README/SKILL.md completeness: Public metadata needs stronger README/SKILL.md context"]},"safety_gate":{"tier":"reviewed","label":"Reviewed","auto_install_policy":"review","auto_install_allowed":false,"human_review_required":true,"blocked":false,"recommended_action":"Review the audit page, then allow agent install in a sandboxed workflow."},"quality":{"score":76,"label":"Strong"},"supply":{"track":"Research and knowledge work","scenario":"Research agents","maintenance":"19d since push","risk":"Safe to try"},"alternative_skills":[],"do_not_use_when":["teams that need a vendor-supported SLA","high-compliance environments without internal security review","No OpenAgentSkill engagement data yet","Quality score needs review","README/SKILL.md completeness: Public metadata needs stronger README/SKILL.md context","Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface","Automatic installation in a production workspace"],"agent_contract":{"task_input":"Use audience-intelligence in an agent workflow","recommended_action":"Review the audit page, then allow agent install in a sandboxed workflow.","install_policy":"review","minimum_review_before_use":["Trust: 80/100 Strong shortlist","Audit: 84/100 Safe to try","Safety: 68/100 Review before install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"indranilbanerjee-audience-intelligence (audience-intelligence)","install_command":"npx skills add indranilbanerjee/digital-marketing-pro --skill audience-intelligence","risk_summary":"Safe to try; Reviewed; Review before production","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"indranilbanerjee-audience-intelligence","task":"Use audience-intelligence in an agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/indranilbanerjee-audience-intelligence","api":"https://www.openagentskill.com/api/agent/skills/indranilbanerjee-audience-intelligence","audit":"https://www.openagentskill.com/skills/indranilbanerjee-audience-intelligence/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=indranilbanerjee-audience-intelligence&task=Use%20audience-intelligence%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20audience-intelligence%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20audience-intelligence%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/indranilbanerjee-audience-intelligence/install","manifest":"https://www.openagentskill.com/api/registry/manifest/indranilbanerjee-audience-intelligence"}},"platforms":["Claude Code"],"use_cases":[{"slug":"research-agents","title":"Research agents","url":"https://www.openagentskill.com/use-cases/research-agents"},{"slug":"marketing-growth","title":"Marketing and growth","url":"https://www.openagentskill.com/use-cases/marketing-growth"},{"slug":"rag-knowledge","title":"RAG and knowledge","url":"https://www.openagentskill.com/use-cases/rag-knowledge"},{"slug":"browser-automation","title":"Browser automation","url":"https://www.openagentskill.com/use-cases/browser-automation"}],"install":"npx skills add indranilbanerjee/digital-marketing-pro --skill audience-intelligence","install_targets":[{"id":"openagentskill-cli","label":"CLI","title":"OpenAgentSkill CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add indranilbanerjee-audience-intelligence","description":"Resolve policy, run the source installer safely, and report a verified install receipt.","copyLabel":"Copy command"},{"id":"codex","label":"Codex","title":"Codex install prompt","kind":"agent-prompt","value":"Install the \"audience-intelligence\" agent skill from https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: 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. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"indranilbanerjee-audience-intelligence\",\"task\":\"Install audience-intelligence\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Give Codex a repo-aware install prompt when the skill is not available through a local CLI.","copyLabel":"Copy prompt"},{"id":"claude-code","label":"Claude Code","title":"Claude Code skill prompt","kind":"agent-prompt","value":"Add \"audience-intelligence\" as a Claude Code skill from https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: 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. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"indranilbanerjee-audience-intelligence\",\"task\":\"Install audience-intelligence\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this prompt to ask Claude Code to add the skill and explain the local activation steps.","copyLabel":"Copy prompt"},{"id":"cursor","label":"Cursor","title":"Cursor rule prompt","kind":"agent-prompt","value":"Turn \"audience-intelligence\" from https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: 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. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"indranilbanerjee-audience-intelligence\",\"task\":\"Install audience-intelligence\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this when installing as Cursor project rules or reusable agent instructions.","copyLabel":"Copy prompt"}],"repository":"https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence","github_repo":"indranilbanerjee/digital-marketing-pro","version":"1.0.0","license":"MIT","updated_at":"2026-09-05T01:43:20.697045+00:00","canonical_key":"indranilbanerjee/digital-marketing-pro#skills/audience-intelligence","recommendation_reasons":["Matches task terms: audience, intelligence","Useful GitHub adoption: 792 stars","Install handoff is available","Repository freshness signal is available","Registry match score 99"],"urls":{"web":"https://www.openagentskill.com/skills/indranilbanerjee-audience-intelligence","api":"https://www.openagentskill.com/api/agent/skills/indranilbanerjee-audience-intelligence","install_api":"https://www.openagentskill.com/api/skills/indranilbanerjee-audience-intelligence/install","audit":"https://www.openagentskill.com/skills/indranilbanerjee-audience-intelligence/audit","repository":"https://github.com/indranilbanerjee/digital-marketing-pro/tree/main/skills/audience-intelligence"}}],"meta":{"endpoint":"/api/skills/search","canonical_agent_endpoint":"/api/agent/resolve","ranking_model":"hybrid-v2-task-fit-quality-outcomes","shortlist_policy":"Return one best match plus up to four distinct alternatives; suppress unrelated direct-name matches.","lookup_intent":true,"exact_match_found":true,"match_counts":{"exact":1,"near":0,"related":0},"no_match_message":null,"safety_policy":"Blocked candidates are excluded by default. Pass include_blocked=true only for manual audit workflows.","agent_friendly":true,"api_version":"1.0","generated_at":"2026-09-06T04:51:35.449Z"}}