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/customer-success-managerWrote 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/customer-success-manager)<a href="https://agentmods.dev/skills/ricneves-ai/flowgrammers-skills/customer-success-manager"><img src="https://agentmods.dev/badge/skills/ricneves-ai/flowgrammers-skills/customer-success-manager/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/customer-success-manager"><img src="https://agentmods.dev/badge/skills/ricneves-ai/flowgrammers-skills/customer-success-manager.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 | $0.00125 | $0.02398 |
| Opus 5 | $0.00063 | $0.01199 |
| Sonnet 5 | $0.00025 | $0.00480 |
| Haiku 4.5 | $0.00013 | $0.00240 |
Grade A, and why
customer-success-manager 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 — 216 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Customer Success Manager
Analytics de sucesso do cliente de nível de produção com pontuação de saúde multidimensional, previsão de risco de churn e identificação de oportunidades de expansão. Três ferramentas Python CLI fornecem análise determinística e repetível usando apenas biblioteca padrão — sem dependências externas, sem chamadas de API, sem modelos de ML.
Sumário
- Requisitos de Entrada
- Formatos de Saída
- Como Usar
- Scripts
- Guias de Referência
- Templates
- Melhores Práticas
- Limitações
Requisitos de Entrada
Todos os scripts aceitam um arquivo JSON como argumento de entrada posicional. Veja assets/sample_customer_data.json para exemplos completos de schema e dados de amostra.
Calculadora de Pontuação de Saúde
Campos obrigatórios por objeto de cliente: customer_id, name, segment, arr e objetos aninhados usage (login_frequency, feature_adoption, dau_mau_ratio), engagement (support_ticket_volume, meeting_attendance, nps_score, csat_score), support (open_tickets, escalation_rate, avg_resolution_hours), relationship (executive_sponsor_engagement, multi_threading_depth, renewal_sentiment) e pontuações previous_period para análise de tendências.
Analisador de Risco de Churn
Campos obrigatórios por objeto de cliente: customer_id, name, segment, arr, contract_end_date e objetos aninhados usage_decline, engagement_drop, support_issues, relationship_signals e commercial_factors.
Pontuador de Oportunidades de Expansão
Campos obrigatórios por objeto de cliente: customer_id, name, segment, arr e objetos aninhados contract (licensed_seats, active_seats, plan_tier, available_tiers), product_usage (sinalizações de adoção e percentuais de uso por módulo) e departments (atuais e potenciais).
Formatos de Saída
Todos os scripts suportam dois formatos de saída via flag --format:
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 · 216 lines · 125 tokens per session scan A ce0eee38d910
customer-success-manager is a skill published in the GitHub repository ricneves-ai/flowgrammers-skills (112 stars, last pushed 3mo ago), licensed MIT. It adds 125 tokens to every session and 2,398 once invoked, about $0.0006 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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