RFP Copilot

# RFP / RFQ Sheet Responder
# Reads questions from Google Sheets, researches each one across Slack and
# approved web domains, synthesizes a submission-ready answer, and writes the
# answer column back to the sheet.

requiredTools:
  - name: slack
    type: mcp
  - name: google-sheets
    type: mcp
  - name: internet_search
    type: internet_search

parameters:
  - name: spreadsheetId
    schema:
      type: string
      description: "Google Sheets spreadsheet ID containing the RFP/RFQ questions"

  - name: questionsRange
    schema:
      type: string
      default: "Sheet1!A2:A100"
      description: "A1 notation range for the questions column, for example 'Sheet1!A2:A100'"

  - name: answersRange
    schema:
      type: string
      default: "Sheet1!B2:B100"
      description: "A1 notation range for the answers column. Must align row-for-row with questionsRange"

  - name: slackChannelIds
    schema:
      type: string
      description: "Comma-separated Slack channel IDs to research, for example 'C012AB3CD,C098ZY7WX'"

  - name: searchDomains
    schema:
      type: string
      description: "Comma-separated domains to search for supporting evidence, for example 'yourcompany.com,docs.yourcompany.com'"

  - name: lookBackDays
    schema:
      type: string
      default: "14"
      description: "Number of days of Slack history to retrieve per channel"

components:
  schemas:
    RfpAnswer:
      type: object
      required:
        - question
        - answer
        - sourceSummary
        - confidence
      properties:
        question:
          type: string
          description: "The original RFP/RFQ question text"
        answer:
          type: string
          description: "Professional submission-ready answer written in first-person plural"
        sourceSummary:
          type: string
          description: "One sentence describing which Slack and web sources informed the answer"
        confidence:
          type: string
          enum: [high, medium, low]
          description: "Confidence based on the quality and specificity of the evidence found"

preCalls:
  - name: computeSlackCutoff
    in: vars
    var: oldestTs
    args:
      days: "{{ .params.lookBackDays }}"
    code: |-
      const days = parseInt(args.days, 10);
      const safeDays = Number.isFinite(days) && days > 0 ? days : 14;
      Math.floor(Date.now() / 1000) - (safeDays * 86400);

  - name: normalizeSlackChannels
    in: vars
    var: slackChannels
    args:
      raw: "{{ .params.slackChannelIds }}"
    code: |-
      String(args.raw || "")
        .split(",")
        .map((value) => value.trim())
        .filter(Boolean);

  - name: normalizeSearchDomains
    in: vars
    var: searchDomainsList
    args:
      raw: "{{ .params.searchDomains }}"
    code: |-
      String(args.raw || "")
        .split(",")
        .map((value) => value.trim())
        .filter(Boolean);

sessions:
  read-rfp-questions:
    tools:
      - name: google-sheets
        type: mcp
    prePrompt: |-
      Use the google-sheets tool to read the spreadsheet with ID "{{ .params.spreadsheetId }}"
      and retrieve the range "{{ .params.questionsRange }}".

      Return the full ordered list of cell values exactly as they appear in the sheet.
      Each non-empty row represents one RFP/RFQ question.
    prompt: |-
      Convert the sheet output into an ordered array of question strings.

      Rules:
      - preserve original row order
      - drop empty rows
      - trim obvious leading/trailing whitespace
      - output only the array of questions

  crawl-slack-per-question:
    dependsOn:
      - session: read-rfp-questions
    context: "{{ .context.questions }}"
    iterateOn: "context.questions"
    tools:
      - name: slack
        type: mcp
    prePrompt: |-
      You are researching evidence for this RFP/RFQ question:
      "{{ .it }}"

      Use the Slack tool to inspect the following channel IDs:
      {{ json .vars.slackChannels }}

      Research window:
      - lookback days: {{ .params.lookBackDays }}
      - oldest timestamp: {{ .vars.oldestTs }}

      Retrieve messages that contain facts, claims, product details, customer outcomes,
      implementation notes, security language, or metrics relevant to this question.

      Include concrete evidence whenever available:
      - message text
      - approximate date
      - channel context
    prompt: |-
      Summarize the strongest Slack evidence for answering:
      "{{ .it }}"

      Requirements:
      - extract only facts or claims useful for the response
      - call out specific numbers, outcomes, or implementation details if present
      - note when evidence is partial or ambiguous
      - if no relevant Slack evidence was found, say that explicitly

  search-web-per-question:
    dependsOn:
      - session: read-rfp-questions
    context: "{{ .context.questions }}"
    iterateOn: "context.questions"
    tools:
      - name: internet_search
        type: internet_search
    prePrompt: |-
      You are researching evidence for this RFP/RFQ question:
      "{{ .it }}"

      Search only within these domains:
      {{ json .vars.searchDomainsList }}

      Run targeted searches that combine the question's concepts with
      site-specific queries where useful.

      Look for:
      - product capabilities
      - architecture or deployment details
      - security or compliance claims
      - case studies
      - documentation
      - support and implementation material
    prompt: |-
      Summarize the best supporting web evidence for answering:
      "{{ .it }}"

      Requirements:
      - surface concrete facts and supporting claims
      - include URLs or page references when available
      - distinguish strong evidence from weak or indirect evidence
      - if nothing relevant was found, say that explicitly

  synthesize-answer-per-question:
    dependsOn:
      - session: crawl-slack-per-question
      - session: search-web-per-question
    context: true
    iterateOn: "context.questions"
    prompt: |-
      You are writing a professional RFP/RFQ response on behalf of the company.

      The question is:
      "{{ .it }}"

      You have two evidence streams in context for this same question:
      1. Slack research from crawl-slack-per-question
      2. Web research from search-web-per-question

      Write a polished answer suitable for direct inclusion in an RFP/RFQ response.

      Answer rules:
      - write in first-person plural
      - answer directly and concisely
      - ground the answer in real evidence from the provided sources
      - if evidence is incomplete, be honest and avoid overclaiming
      - never fabricate metrics, certifications, or specifics

      Confidence rubric:
      - high: strong and specific evidence backs the answer
      - medium: partial but meaningful evidence supports the answer
      - low: weak evidence; answer is best-effort and carefully qualified

      Map the output exactly to the RfpAnswer schema:
      - question
      - answer
      - sourceSummary
      - confidence

  write-answers-to-sheet:
    dependsOn:
      - session: synthesize-answer-per-question
    context: true
    tools:
      - name: google-sheets
        type: mcp
    prePrompt: |-
      Use the google-sheets tool to write answer text back to the spreadsheet.

      Inputs:
      - Spreadsheet ID: {{ .params.spreadsheetId }}
      - Target range: {{ .params.answersRange }}

      The synthesized answers are available in context under "answers".
      Write only the "answer" field from each answer object.

      Preserve original question order and write as a single answer column.
      Use RAW value input mode if the tool supports it.
    prompt: |-
      Confirm the write result.

      Return:
      - rowsWritten
      - spreadsheetId
      - rangeWritten
      - errors

      If all writes succeeded, return an empty errors array.

schema:
  type: object
  properties:
    questions:
      x-session: read-rfp-questions
      type: array
      items:
        type: string
      description: "Ordered list of questions read from the sheet"

    slackEvidence:
      x-session: crawl-slack-per-question
      type: array
      items:
        type: string
      description: "Per-question Slack evidence summaries aligned to the original question order"

    webEvidence:
      x-session: search-web-per-question
      type: array
      items:
        type: string
      description: "Per-question web evidence summaries aligned to the original question order"

    answers:
      x-session: synthesize-answer-per-question
      type: array
      items:
        $ref: "#/components/schemas/RfpAnswer"
      description: "Synthesized RFP/RFQ answers in original row order"

    writeConfirmation:
      x-session: write-answers-to-sheet
      type: object
      properties:
        rowsWritten:
          type: integer
          description: "Number of answer rows successfully written"
        spreadsheetId:
          type: string
          description: "Spreadsheet that was updated"
        rangeWritten:
          type: string
          description: "The actual A1 range written"
        errors:
          type: array
          items:
            type: string
          description: "Row-level or sheet-level write failures"