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/sales-engineerWrote 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/sales-engineer)<a href="https://agentmods.dev/skills/ricneves-ai/flowgrammers-skills/sales-engineer"><img src="https://agentmods.dev/badge/skills/ricneves-ai/flowgrammers-skills/sales-engineer/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/sales-engineer"><img src="https://agentmods.dev/badge/skills/ricneves-ai/flowgrammers-skills/sales-engineer.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 | $0.00171 | $0.02563 |
| Opus 5 | $0.00086 | $0.01282 |
| Sonnet 5 | $0.00034 | $0.00513 |
| Haiku 4.5 | $0.00017 | $0.00256 |
Grade A, and why
sales-engineer 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 — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill de Sales Engineer
Fluxo de Trabalho em 5 Fases
Fase 1: Descoberta e Pesquisa
Objetivo: Entender os requisitos do cliente, ambiente técnico e drivers de negócio.
Lista de Verificação:
- Conduzir chamadas de descoberta técnica com partes interessadas
- Mapear a arquitetura atual do cliente e pontos de dor
- Identificar requisitos de integração e restrições
- Documentar requisitos de segurança e conformidade
- Avaliar o cenário competitivo para esta oportunidade
Ferramentas: Executar rfp_response_analyzer.py para pontuar o alinhamento inicial de requisitos.
python scripts/rfp_response_analyzer.py assets/sample_rfp_data.json --format json > phase1_rfp_results.json
Saída: Documento de descoberta técnica, mapa de requisitos, avaliação inicial de cobertura.
Ponto de verificação de validação: A pontuação de cobertura deve ser >50% e lacunas obrigatórias ≤3 antes de prosseguir para a Fase 2. Verificar com:
python scripts/rfp_response_analyzer.py assets/sample_rfp_data.json --format json | python -c "import sys,json; r=json.load(sys.stdin); print('PROSSEGUIR' if r['coverage_score']>50 and r['must_have_gaps']<=3 else 'REVISAR')"
Fase 2: Design da Solução
Objetivo: Projetar uma arquitetura de solução que atenda aos requisitos do cliente.
Lista de Verificação:
- Mapear capacidades do produto para os requisitos do cliente
- Projetar arquitetura de integração
- Identificar necessidades de customização e esforço de desenvolvimento
- Construir estratégia de diferenciação competitiva
- Criar diagramas de arquitetura da solução
Ferramentas: Executar competitive_matrix_builder.py usando dados da Fase 1 para identificar diferenciadores e vulnerabilidades.
python scripts/competitive_matrix_builder.py competitive_data.json --format json > phase2_competitive.json
python -c "import json; d=json.load(open('phase2_competitive.json')); print('Diferenciadores:', d['differentiators']); print('Vulnerabilidades:', d['vulnerabilities'])"
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 · 228 lines · 171 tokens per session scan A bae639d93fae
sales-engineer is a skill published in the GitHub repository ricneves-ai/flowgrammers-skills (112 stars, last pushed 3mo ago), licensed MIT. It adds 171 tokens to every session and 2,563 once invoked, about $0.0009 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.
Other skills, from other repositories
baoyu-youtube-transcript
A tool for downloading the written captions, subtitles, chapter information, speaker labels, and cover image from a YouTube video using its URL or ID.
orbit-notion
Open Orbit briefing skill — selected by the Orbit pipeline when Notion is the user's only connected connector, or when the user explicitly scopes their daily digest to Notion. Pulls the past 24 hours of document edits, comments, mentions, and database row changes from the user's authenticated Notion connection and…
instrument-data-to-allotrope
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…
feishu
Work with Feishu or Lark bots, docs, sheets, bitables, approval flows, and OpenAPI/MCP setup without hardcoding credentials.
read
Reads URLs and PDFs by fetching source content, defaulting to concise summaries for plain read requests and clean Markdown when asked to convert, save, quote, cite, or feed downstream work. Use when users ask in any language to read, fetch, check, summarize, quote, cite, convert, or save a URL or PDF. Not for local…
overleaf-sync
A two-way connection between a local paper folder and Overleaf, a web-based LaTeX editor for writing research papers. It lets you move changes between the local files and the shared Overleaf project.