Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/ricneves-ai/flowgrammers-skillsnpx agentmods add skills/ricneves-ai/flowgrammers-skills/revenue-operationsWrote 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/ricneves-ai/flowgrammers-skills/revenue-operations)<a href="https://agentmods.dev/skills/ricneves-ai/flowgrammers-skills/revenue-operations"><img src="https://agentmods.dev/badge/skills/ricneves-ai/flowgrammers-skills/revenue-operations/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/ricneves-ai/flowgrammers-skills/revenue-operations"><img src="https://agentmods.dev/badge/skills/ricneves-ai/flowgrammers-skills/revenue-operations.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 | $0.00089 | $0.02711 |
| Opus 5 | $0.00044 | $0.01355 |
| Sonnet 5 | $0.00018 | $0.00542 |
| Haiku 4.5 | $0.00009 | $0.00271 |
Grade A, and why
revenue-operations 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 12d 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 — 276 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Revenue Operations
Análise de pipeline, rastreamento de precisão de previsão e medição de eficiência GTM para equipes de receita SaaS.
Formatos de saída: Todos os scripts suportam
--format text(legível por humanos) e--format json(painéis/integrações).
Início Rápido
# Analisar saúde e cobertura do pipeline
python scripts/pipeline_analyzer.py --input assets/sample_pipeline_data.json --format text
# Rastrear precisão de previsão ao longo de múltiplos períodos
python scripts/forecast_accuracy_tracker.py assets/sample_forecast_data.json --format text
# Calcular métricas de eficiência GTM
python scripts/gtm_efficiency_calculator.py assets/sample_gtm_data.json --format text
Visão Geral das Ferramentas
1. Analisador de Pipeline
Analisa saúde do pipeline de vendas incluindo taxas de cobertura, taxas de conversão por estágio, velocidade de negócio, riscos de envelhecimento e riscos de concentração.
Entrada: Arquivo JSON com negócios, cota e configuração de estágio Saída: Taxas de cobertura, taxas de conversão, métricas de velocidade, sinalizações de envelhecimento, avaliação de riscos
Uso:
python scripts/pipeline_analyzer.py --input pipeline.json --format text
Principais Métricas Calculadas:
- Taxa de Cobertura do Pipeline — Valor total do pipeline / meta de cota (saudável: 3-4x)
- Taxas de Conversão por Estágio — Taxas de progressão de estágio para estágio
- Velocidade de Vendas — (Oportunidades x Tamanho Médio do Negócio x Taxa de Vitória) / Ciclo Médio de Vendas
- Envelhecimento de Negócios — Sinaliza negócios que excedem 2x o tempo médio de ciclo por estágio
- Risco de Concentração — Avisa quando >40% do pipeline está em um único negócio
- Análise de Lacuna de Cobertura — Identifica trimestres com pipeline insuficiente
Schema de Entrada:
{
"quota": 500000,
"stages": ["Discovery", "Qualification", "Proposal", "Negotiation", "Closed Won"],
"average_cycle_days": 45,
"deals": [
{
"id": "D001",
"name": "Empresa ABC",
"stage": "Proposal",
"value": 85000,
"age_days": 32,
"close_date": "2025-03-15",
"owner": "rep_1"
}
]
}
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.
- 12d ago First seen · 276 lines · 89 tokens per session scan A 461abe22125e
revenue-operations is a skill published in the GitHub repository ricneves-ai/flowgrammers-skills (112 stars, last pushed 3mo ago), licensed MIT. It adds 89 tokens to every session and 2,711 once invoked, about $0.0004 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 2026-08-30.
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