Cowork Rfp Response

Organization

OneWave-AI

cowork-rfp-response

Turn an RFP and a folder of your past proposals, case studies, and capability docs into a requirement-by-requirement compliance matrix and a drafted response. Flags disqualifiers and unanswerable requirements before you burn a week writing.

Overview

Publisher	OneWave-AI
Repository	`claude-skills`
Skill name	`cowork-rfp-response`
Stars	293
Forks	49
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by OneWave-AI on GitHub. Read the source before you install it.

Installation

Install the Cowork Rfp Response AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/OneWave-AI/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/cowork-rfp-response .claude/skills/cowork-rfp-response

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cowork Rfp Response in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cowork Rfp Response on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cowork Rfp Response is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Cowork RFP Response

Respond to an RFP the way a seasoned proposal manager does: decompose every requirement first, decide bid/no-bid honestly, reuse the best prior language, and never claim a capability the source documents do not support. Inputs: the RFP document and a folder of company material (past proposals, case studies, bios, certifications, pricing sheets).

Workflow

Shred the RFP. Extract every numbered and implied requirement into a matrix: ID, requirement text (verbatim), type (mandatory/scored/informational), section owner, and any disqualifier ("must have X certification", "minimum N years"). Extract the logistics separately: due date, format, page limits, submission method, Q&A deadline, evaluation criteria and weights.
Bid/no-bid check. Before drafting anything, report disqualifiers you cannot document from the company folder and requirements with weak evidence. Ask whether to proceed. This is the most valuable five minutes of the skill.
Mine the folder. For each requirement, find the strongest supporting material: prior proposal sections, case studies with named results, team bios, certifications. Record source file and section in the matrix. Mark each requirement STRONG (direct evidence), PARTIAL (adjacent evidence, needs framing), or GAP (nothing found).
Draft. Write the response following the RFP's mandated structure exactly. For STRONG items, adapt the best prior language to this client's context. For PARTIAL, draft honest framing and flag it for review. For GAP, insert a clearly marked [GAP: needs input -- suggested approach] block rather than fiction.
Compliance pass. Verify every mandatory requirement is addressed where the RFP says it must be, page/format limits hold, and required attachments are listed. Output compliance-matrix.md (the full matrix with response locations) and rfp-response-draft.md.
Executive summary last. Write it after the body, leading with the client's stated problem in their own vocabulary and the 2-3 discriminators the evidence actually supports.

Rules

Never invent capabilities, clients, metrics, or certifications. Every claim traces to a source file; GAP blocks are the honest alternative.
Use the client's terminology from the RFP, not internal jargon. Evaluators score against their own words.
Answer the requirement asked, not the adjacent one you have better material for -- then add the better material.
Respect page limits from the first draft; cutting 40% at the end butchers the good sections.
Boilerplate is a starting point, not a deliverable. Any reused paragraph must name this client and this context or it gets rewritten.
Track questions for the Q&A window: ambiguous requirements go in a questions-to-submit.md list, drafted in submission-ready form.

Quick Commands

"Shred [RFP file]" -- requirements matrix and logistics only
"Should we bid?" -- steps 1-3, the honest gap report
"Full response with [folder]" -- complete workflow
"Compliance check my draft" -- step 5 against an existing draft

Frequently asked questions

What does the Cowork Rfp Response AI skill do?

Why use Cowork Rfp Response on TypingMind?

Because you install it once and use it with any model. Cowork Rfp Response is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Cowork Rfp Response in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/OneWave-AI/claude-skills/tree/main/cowork-rfp-response. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Cowork Rfp Response?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Cowork Rfp Response?

As many as you like. As long as a model supports skills, you can use Cowork Rfp Response with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cowork Rfp Response AI skill free?

Yes. It is published on GitHub by OneWave-AI under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Cowork RFP Response

Workflow

Rules

Quick Commands

Frequently asked questions

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