Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add lckx777/copy-chief-black --skill audience-research-agentgit clone --depth 1 https://github.com/lckx777/copy-chief-blackWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/lckx777/copy-chief-black/audience-research-agent)<a href="https://agentmods.dev/skills/lckx777/copy-chief-black/audience-research-agent"><img src="https://agentmods.dev/badge/skills/lckx777/copy-chief-black/audience-research-agent/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/lckx777/copy-chief-black/audience-research-agent"><img src="https://agentmods.dev/badge/skills/lckx777/copy-chief-black/audience-research-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00063 | $0.04808 |
| Opus 5 | $0.00032 | $0.02404 |
| Sonnet 5 | $0.00013 | $0.00962 |
| Haiku 4.5 | $0.00006 | $0.00481 |
Grade A, and why
audience-research-agent scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 487 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Audience Research Agent
Copy Chief estratégico responsável por coordenar pesquisa de público em 4 fases, delegar extração técnica ao voc-research-agent, aplicar frameworks de análise psicográfica na Fase 3, e gerar VOC Library RAG-otimizada para outros agentes.
Quick Start
- Receber materiais da oferta (produto, avatar inicial, concorrentes)
- Executar 4 fases: Análise → Extração VOC → Síntese Psicográfica → Output
- Gerar VOC Library YAML com Score de Prontidão ≥70/100
→ Output:
voc_library_[nicho]_[data].yamlpronto para HELIX/criativos
Output Location
Write all outputs to:
- Raw VOC:
research/{offer-name}/voc/raw/— Extração bruta por plataforma - Processed:
research/{offer-name}/voc/processed/pain-points.md— Dores classificadas por intensidadedesires.md— Desejos declarados/implícitos/secretosobjections.md— Objeções mapeadas com counterslanguage-patterns.md— Expressões e hooks verbatim
- Summary:
research/{offer-name}/voc/summary.md— MAX 500 tokens - VOC Library:
research/{offer-name}/voc_library.yaml— Arquivo completo
CRITICAL: Return only summary.md path to orchestrator. Never return raw content.
Quando Usar
Ativar para pesquisa profunda de público-alvo além de personas superficiais, extração de dores viscerais e linguagem natural, briefing psicográfico para VSL/landing page/campanha, ou preparação de inputs para helix-system-agent ou criativos-agent.
Workflow de 4 Fases
Fase 1 - Análise de Inputs
Objetivo: Coletar e processar materiais existentes ANTES de iniciar pesquisa. Estabelecer baseline que guia a Fase 2.
Prompt de Intake (usar ao iniciar):
## FASE 1: COLETA DE INPUTS
Antes de iniciar a pesquisa VOC, preciso de contexto sobre a oferta.
### Materiais Existentes (se houver)
- VSL/TSL atual? (link ou arquivo)
- Landing page? (link)
- Criativos rodando? (prints, links, ou arquivo consolidado)
- Materiais de referência/mineração?
### Informações do Produto
- Nome da oferta:
- Tipo (VSL/TSL/SaaS/Curso/Ebook):
- Faixa de preço:
- Expert/fundador (se houver):
- Promessa central (1 frase):
### Contexto de Mercado
- Concorrentes conhecidos:
- O que já funciona/não funciona (se souber):
- Nicho/sub-nicho específico:
[Após receber inputs, gerar research/fase-01-inputs.md]
What ships with it
24 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- CLAUDE.md 18 B
- references/aula_01_principios_fundamentais.md 29 KB
- references/aula_02_psicologia_engenheiro.md 9.0 KB
- references/aula_04_puzzle_pieces.md 14 KB
- references/aula_geral_comunicacao_pedreiro_01_intro_conversa.md 2.8 KB
- references/aula_geral_comunicacao_pedreiro_02_ritmo_sensorial.md 2.8 KB
- references/aula_geral_comunicacao_pedreiro_03_metodo_abc.md 2.8 KB
- references/aula_geral_comunicacao_pedreiro_04_edicao_camadas.md 4.5 KB
- references/aula_geral_comunicacao_pedreiro_05_problemas_recursos.md 6.3 KB
- references/ref_frameworks_georgi_evaldo_makepeace_ramalho_schwartz.md 9.5 KB
- references/ref_frameworks_jtbd_robbins_kahneman_empathy.md 7.4 KB
- references/ref_gatilhos_reptilianos_10.md 874 B
- references/ref_platform_amazon.md 1.8 KB
- references/ref_platform_instagram.md 4.9 KB
- references/ref_platform_mercadolivre.md 5.6 KB
- references/ref_platform_reclameaqui.md 6.7 KB
- references/ref_platform_reddit.md 2.5 KB
- references/ref_platform_tiktok.md 5.0 KB
- references/ref_platform_youtube.md 4.4 KB
- references/ref_readiness_score_5_dimensions.md 9.4 KB
- references/ref_voc_database_schema.md 10 KB
- references/ref_voc_sources_rules_templates.md 8.3 KB
- references/ref_workflow_modular_4_modules.md 12 KB
- templates/fase-01-inputs-template.md 5.2 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 487 lines · 63 tokens per session scan A 3ecc5a25cb86
audience-research-agent is a skill published in the GitHub repository lckx777/copy-chief-black (5 stars, last pushed 6mo ago), licensed MIT. It adds 63 tokens to every session and 4,808 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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