Doc Coauthoring
aws-samples/sample-strands-agent-with-agentcore
Guide users through a structured workflow for co-authoring documentation.
Create tailored sales proposals and RFP responses that address prospect needs, articulate solution value, and include pricing, timelines, and social proof.
Install Proposal Generation
$ npx skills add seb1n/awesome-ai-agent-skills --skill proposal-generation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills proposal-generation --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/sales/proposal-generation .claude/skills/proposal-generation && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "proposal-generation" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/sales/proposal-generation into .claude/skills/proposal-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "proposal-generation", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/seb1n/awesome-ai-agent-skills/tree/main/sales/proposal-generationType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add seb1n/awesome-ai-agent-skills --skill proposal-generation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills proposal-generation --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/sales/proposal-generation .agents/skills/proposal-generation && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "proposal-generation" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/sales/proposal-generation into .agents/skills/proposal-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "proposal-generation", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add seb1n/awesome-ai-agent-skills --skill proposal-generation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills proposal-generation --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/sales/proposal-generation .cursor/skills/proposal-generation && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "proposal-generation" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/sales/proposal-generation into .cursor/skills/proposal-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "proposal-generation", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/seb1n/awesome-ai-agent-skills.git --path sales/proposal-generation--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add seb1n/awesome-ai-agent-skills --skill proposal-generation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills proposal-generation --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/sales/proposal-generation .gemini/skills/proposal-generation && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "proposal-generation" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/sales/proposal-generation into .gemini/skills/proposal-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "proposal-generation", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install seb1n/awesome-ai-agent-skills proposal-generationInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add seb1n/awesome-ai-agent-skills --skill proposal-generation -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/sales/proposal-generation .github/skills/proposal-generation && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "proposal-generation" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/sales/proposal-generation into .github/skills/proposal-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "proposal-generation", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add seb1n/awesome-ai-agent-skills --skill proposal-generation -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills proposal-generation --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/sales/proposal-generation .opencode/skills/proposal-generation && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "proposal-generation" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/sales/proposal-generation into .opencode/skills/proposal-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "proposal-generation", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
proposal-generation- GitHub stars
- 206
- Token cost
- ~1.7k tokens
- SKILL.md length
- 832 words
- Files
- 1
- Skills in repo
- 91
- Repo updated
- First seen
- Licence
- MIT
At a glance
Create tailored sales proposals and RFP responses that address prospect needs, articulate solution value, and include pricing, timelines, and social proof.
- Works in 6 steps: Analyze Requirements or RFP — Parse the… → Research the Prospect — Gather… → Draft the Executive Summary — Write a… → …
- The user requests proposal generation
- SKILL.md covers Workflow, Usage, Examples and Best Practices, plus 1 more section
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Proposal Generation is an agent skill from seb1n/awesome-ai-agent-skills. Create tailored sales proposals and RFP responses that address prospect needs, articulate solution value, and include pricing, timelines, and social proof. Use when the user requests proposal generation or provides relevant inputs for this workflow.
Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Sales & Support, covering Proposals and quotes. The repository describes itself as: 103 ready-to-use AI agent skills for Claude Code, OpenAI Codex, Gemini CLI, Cursor, GitHub Copilot, Windsurf, and other Agent Skills-compatible tools. Complete SKILL.md… The licence is MIT.
When your agent uses it
- The user requests proposal generation
- Provides relevant inputs for this workflow
Example prompts
- “/proposal-generation”
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- Analyze Requirements or RFP — Parse the prospect's RFP document, requirements list, or briefing notes to extract mandatory criteria…
- Research the Prospect — Gather firmographic data (revenue, headcount, industry vertical), recent news, strategic initiatives, and known…
- Draft the Executive Summary — Write a concise summary (250–400 words) that mirrors the prospect's language, restates their core challenge…
- Detail Solution and Pricing — Map each requirement to a specific product capability or service offering. Build a pricing table with line…
- Add Case Studies and Social Proof — Select 2–3 case studies from similar industries or company sizes. For each, include the customer's…
- Format and Finalize the Deliverable — Assemble the proposal into the required format (PDF, DOCX, slide deck). Apply brand guidelines…
What it can do on your machine
Read from SKILL.md and the folder at commit 75865a5. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Proposal Generation loads about 1.7k tokens when it runs. Until then it costs about 67 tokens; SKILL.md has 832 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from seb1n/awesome-ai-agent-skills at commit 75865a5, republished under its MIT licence (© seb1n). 832 words, ~1,694 tokens.
Download SKILL.mdSave it as
.claude/skills/proposal-generation/SKILL.md (or your agent's skills folder).- name
- proposal-generation
- description
- Create tailored sales proposals and RFP responses that address prospect needs, articulate solution value, and include pricing, timelines, and social proof. Use when the user requests proposal generation or provides relevant inputs for this workflow.
- license
- MIT
- metadata.author
- community
- metadata.version
- 1.0
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
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.
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.
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.
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.
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.
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.
Usage
Provide the prospect's requirements or RFP text, your company's solution details, and any relevant case studies. Optionally specify the output format and tone.
Example prompt:
Generate a sales proposal for Acme Corp, a 500-person logistics company evaluating our warehouse management SaaS. Their RFP requires cloud deployment, real-time inventory tracking, and ERP integration. Budget range is $80K–$120K/year. Include executive summary, solution mapping, pricing, timeline, and at least two case studies.
Examples
Example 1: SaaS Implementation Proposal
Input: Proposal for Acme Corp (logistics, 500 employees, $80K–$120K budget) evaluating warehouse management SaaS.
Output:
Executive Summary
Acme Corp's rapid expansion across three distribution centers has exposed visibility gaps in inventory accuracy and order fulfillment speed. Our Warehouse Management Platform delivers real-time inventory tracking, automated replenishment triggers, and native ERP integration — enabling logistics teams to reduce stockouts by 34% and cut fulfillment cycle time by 22%, based on results from comparable deployments. This proposal outlines a phased rollout that meets Acme's cloud-first mandate and delivers measurable ROI within 90 days of go-live.
Solution Overview
| Requirement | Capability | Details |
|---|---|---|
| Cloud deployment | Multi-tenant AWS infrastructure | SOC 2 Type II certified, 99.95% uptime SLA |
| Real-time inventory | IoT sensor integration + live dashboards | Sub-second updates across all warehouse zones |
| ERP integration | Pre-built SAP and Oracle connectors | Bi-directional sync with < 5-minute latency |
Pricing
| Item | Annual Cost |
|---|---|
| Platform license (up to 500 users) | $72,000 |
| ERP integration module | $18,000 |
| Premium support (24/7) | $12,000 |
| Total | $102,000 |
Timeline
- Weeks 1–2: Discovery and configuration
- Weeks 3–5: ERP integration and data migration
- Week 6: UAT and training
- Week 7: Go-live at primary DC
- Weeks 8–10: Rollout to remaining DCs
Show full SKILL.md (289 more words)Show less
Example 2: RFP Compliance Response
Input: Answer Section 4.2 of an RFP on data security and compliance for a healthcare prospect.
Output:
Section 4.2 — Data Security & Compliance
| # | Requirement | Response | Compliance |
|---|---|---|---|
| 4.2.1 | HIPAA BAA execution | We execute BAAs with all healthcare customers prior to data onboarding. | ✅ Full |
| 4.2.2 | Data encryption at rest | AES-256 encryption on all data stores, key management via AWS KMS. | ✅ Full |
| 4.2.3 | Annual penetration testing | Conducted by independent third party (NCC Group); most recent report available under NDA. | ✅ Full |
| 4.2.4 | Data residency in US | All data stored in AWS us-east-1 and us-west-2 regions. No cross-border transfer. | ✅ Full |
| 4.2.5 | Role-based access control | Granular RBAC with SSO (SAML 2.0/OIDC) and mandatory MFA for admin roles. | ✅ Full |
Best Practices
- Mirror the prospect's terminology and priorities — don't make them translate your jargon.
- Lead every section with the business outcome, not the feature description.
- Keep pricing transparent; hidden costs erode trust faster than higher sticker prices.
- Quantify ROI with metrics from real deployments, not theoretical projections.
- Tailor case studies to the prospect's industry and company size for maximum relevance.
- Have a clear call-to-action and defined next steps at the end of every proposal.
Edge Cases
- Incomplete RFP requirements — When the RFP is vague or missing sections, document assumptions explicitly and include a clarification questions appendix.
- No matching case studies — Use adjacent-industry examples and emphasize transferable outcomes; disclose the industry difference upfront.
- Multi-stakeholder conflicting priorities — Create stakeholder-specific sections (e.g., a technical appendix for IT, an ROI summary for finance) within the same proposal.
- Strict page or word limits — Prioritize executive summary and solution fit; move detailed specs to a separately referenced appendix.
- Competitor-specific evaluation criteria — When RFP criteria clearly favor a competitor's architecture, address the requirement honestly and reframe around your differentiated strengths.
© seb1n, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in sales/proposal-generation of seb1n/awesome-ai-agent-skills.
Open the folder on GitHubat commit 75865a5
Compare with similar skills
Proposal Generation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Proposal Generation this skillseb1n/awesome-ai-agent-skills | 206 | — | ~1.7k | Automated safety check: Pass | MIT | |
| Doc Coauthoringaws-samples/sample-strands-agent-with-agentcore | 195 | 40 repos | ~3.2k | Automated safety check: Pass | MIT | |
| Audit Onboarding Proposalhoangnb24/repository-harness | 1.2k | — | ~4k | Automated safety check: Pass | MIT | |
| No Negative EchoLB623/no-negative-echo | 897 | — | ~965 | Automated safety check: Pass | MIT | |
| GEO Service Proposal Generatorzubair-trabzada/geo-seo-claude | 11k | — | ~3k | Automated safety check: Notes | MIT | |
| Architectural ProposalsFritzAndFriends/SharpSite | 145 | 2 repos | ~1.6k | Automated safety check: Pass | MIT |
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Categories
Questions about Proposal Generation
What does Proposal Generation do?
Create tailored sales proposals and RFP responses that address prospect needs, articulate solution value, and include pricing, timelines, and social proof. Proposal Generation is an agent skill from seb1n/awesome-ai-agent-skills. Create tailored sales proposals and RFP responses that address prospect needs, articulate solution value, and include pricing, timelines, and social proof.
When should I use Proposal Generation?
Proposal Generation fits situations like: the user requests proposal generation; provides relevant inputs for this workflow.
How do I install Proposal Generation in Claude Code?
Run `npx skills add seb1n/awesome-ai-agent-skills --skill proposal-generation -a claude-code`. Or copy the skill folder (sales/proposal-generation in seb1n/awesome-ai-agent-skills) into .claude/skills/proposal-generation in your project. Claude Code loads it when a task matches its description.
How do I install Proposal Generation in Codex?
Run `npx skills add seb1n/awesome-ai-agent-skills --skill proposal-generation -a codex`. Or copy the skill folder (sales/proposal-generation in seb1n/awesome-ai-agent-skills) into .agents/skills/proposal-generation in your project. Codex loads it when a task matches its description.
Can I use Proposal Generation in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add seb1n/awesome-ai-agent-skills --skill proposal-generation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/proposal-generation, .gemini/skills/proposal-generation, .github/skills/proposal-generation and .opencode/skills/proposal-generation in your project.
What does Proposal Generation need to run?
SKILL.md names no scripts, command-line tools or credentials: Proposal Generation is instructions for the agent only.
Does Proposal Generation access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Proposal Generation safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Proposal Generation use?
Proposal Generation is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Proposal Generation use?
About 1.7k tokens (SKILL.md is roughly 6.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Proposal Generation?
Skills that share tags, products or a category with Proposal Generation: Doc Coauthoring (aws-samples/sample-strands-agent-with-agentcore, 195 stars), Audit Onboarding Proposal (hoangnb24/repository-harness, 1.2k stars), No Negative Echo (LB623/no-negative-echo, 897 stars) and GEO Service Proposal Generator (zubair-trabzada/geo-seo-claude, 11k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Proposal Generation?
seb1n (a GitHub user) maintains it in seb1n/awesome-ai-agent-skills, which has 206 GitHub stars. The repository holds 91 skills in this directory. The repository was last updated on August 9, 2026.
Source: seb1n/awesome-ai-agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.