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 seb1n/awesome-ai-agent-skills --skill proposal-generationgit clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skillsWrote 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/seb1n/awesome-ai-agent-skills/proposal-generation)<a href="https://agentmods.dev/skills/seb1n/awesome-ai-agent-skills/proposal-generation"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/proposal-generation/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/seb1n/awesome-ai-agent-skills/proposal-generation"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/proposal-generation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00045 | $0.01432 |
| Opus 5 | $0.00023 | $0.00716 |
| Sonnet 5 | $0.00009 | $0.00286 |
| Haiku 4.5 | $0.00005 | $0.00143 |
Grade A, and why
proposal-generation 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 — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sales Proposal Generation
Generate compelling, customized sales proposals and RFP responses from prospect requirements. This skill analyzes buyer needs, maps your solution to their pain points, structures executive summaries, pricing tables, implementation timelines, and weaves in relevant case studies to maximize win rates.
Workflow
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Analyze Requirements or RFP — Parse the prospect's RFP document, requirements list, or briefing notes to extract mandatory criteria, evaluation weightings, submission formatting rules, and any compliance requirements. Categorize items as must-have vs. nice-to-have and flag disqualification risks early.
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Research the Prospect — Gather firmographic data (revenue, headcount, industry vertical), recent news, strategic initiatives, and known technology stack. Identify the decision-making unit — economic buyer, champion, technical evaluator — and tailor messaging to each stakeholder's priorities.
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Draft the Executive Summary — Write a concise summary (250–400 words) that mirrors the prospect's language, restates their core challenge, positions your solution as the best fit, and previews quantified business outcomes. This section sells the rest of the proposal.
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Detail Solution and Pricing — Map each requirement to a specific product capability or service offering. Build a pricing table with line items, optional tiers, and volume discounts. Include an implementation timeline with milestones, dependencies, and resource assumptions.
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Add Case Studies and Social Proof — Select 2–3 case studies from similar industries or company sizes. For each, include the customer's challenge, the solution deployed, and measurable results (revenue lift, cost savings, time-to-value). Append relevant logos, testimonials, or analyst quotes.
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Format and Finalize the Deliverable — Assemble the proposal into the required format (PDF, DOCX, slide deck). Apply brand guidelines, insert a table of contents, add appendices for technical specs or SLAs, and run a compliance checklist to ensure every RFP question is answered.
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 · 104 lines · 45 tokens per session scan A bd2847817b78
proposal-generation is a skill published in the GitHub repository seb1n/awesome-ai-agent-skills (179 stars, last pushed 1mo ago), licensed MIT. It adds 45 tokens to every session and 1,432 once invoked, about $0.0002 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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