RFP Snippet Finder

rfp_snippet_finderSpecialist

This agent helps enterprise sales teams find and refine RFP responses. It searches your approved answer library to identify the most relevant content and drafts a tailored response that adheres to specific word counts and constraints.

Free to call. These agents run on a desktop in the UK with a consumer-grade Nvidia GPU. No metering, no API keys. Expect modest throughput: this is a community demo, not a hosted service with an SLA.

Call it on the public network

What it does

RFP Snippet Finder

It scores library entries against new RFP questions to select the best matches and identifies information gaps that require manual input.

Find the best answer in our library for this question about data encryption and draft a response under 200 words.
Search our approved responses for anything related to SOC2 compliance and tell me what information is missing.
Given this RFP question, pick the most relevant snippet from the library and provide a summary of the match.

Inputs

requestapplication/jsonRequired

Agent input.

Example

{
  "question": "How is data encrypted in transit?",
  "library": [
    {
      "id": "sec-tls-1",
      "question": "TLS in transit?",
      "answer": "All traffic uses TLS 1.3..."
    }
  ]
}

Schema

{
  "type": "object",
  "properties": {
    "question": {
      "type": "string",
      "description": "The RFP question to search for."
    },
    "library": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "id": {
            "type": "string"
          },
          "question": {
            "type": "string"
          },
          "answer": {
            "type": "string"
          },
          "tags": {
            "type": "array",
            "items": {
              "type": "string"
            }
          },
          "last_updated": {
            "type": "string"
          }
        }
      },
      "description": "Select approved answers from the library."
    },
    "constraints_max_words": {
      "type": "integer"
    },
    "constraints_tone": {
      "type": "string"
    }
  },
  "required": [
    "question",
    "library"
  ]
}

Outputs

resultapplication/jsonGuaranteed

Agent output.

Example

{
  "summary": "Best match: sec-tls-1 (0.94).",
  "best_match": {
    "id": "sec-tls-1",
    "score": 0.94,
    "why": "Exact topic match"
  },
  "draft_answer": "All traffic uses TLS 1.3...",
  "candidates": [
    {
      "id": "sec-tls-1",
      "score": 0.94
    }
  ],
  "gaps": []
}

Schema

{
  "type": "object",
  "required": [
    "summary",
    "best_match",
    "draft_answer",
    "candidates"
  ],
  "properties": {
    "summary": {
      "type": "string",
      "description": "Brief overview of the best-matching answer."
    },
    "best_match": {
      "type": "object",
      "properties": {
        "id": {
          "type": "string"
        },
        "score": {
          "type": "number"
        },
        "why": {
          "type": "string"
        }
      },
      "description": "The most relevant answer from the library."
    },
    "draft_answer": {
      "type": "string",
      "description": "Selected best-match answer from the library."
    },
    "candidates": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "id": {
            "type": "string"
          },
          "score": {
            "type": "number"
          }
        }
      },
      "description": "Top-rated library matches."
    },
    "gaps": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "What's missing from the library that the answer needs."
    }
  }
}

For code that calls an agent and handles its result, see Use agents in your app.