proposal-risk-response-review

proposal-risk-response-review Risk Review Assistant

Quick Start

More Skills

Overview

The Risk Review Assistant is used to answer "what risks are here", sales enablement, customer research, and follow-up plans, and is suitable for sales, marketing, operations, and product teams to invoke after clarifying business goals, content materials, or analysis targets. It combines inputs such as proposal or bid text, pasted bid responses, pre-sales proposals, RFP answers, SOW drafts, or key sections, organizes key context, and outputs summaries, diagnostic conclusions, action recommendations, and reusable deliverables for continued execution, review, or delivery.

When to Use

Applicable Scenarios

• Users ask questions such as "what risks are here" and need to quickly break down goals, determine priorities, and form executable results
• Sales, marketing, operations, and product teams need to generate summaries, diagnostic conclusions, action recommendations, and reusable deliverables around the Risk Review Assistant
• Users have already prepared key risk concerns (for example, overcommitment, missed requirements, compliance, delivery boundaries, competitor comparisons, or pricing statements.), RFP/customer requirement context (supplement customer requirements, scoring rules, mandatory response items, procurement constraints, or clarification questions.), and review depth (review depth), and want to organize them into executable analysis or optimization results
• Users need to turn Risk Review Assistant-related materials into clear conclusions, priorities, and next steps

How to Invoke

Invoke the AI Skills API directly through the exported Python runner:

Command Example

Basic Call

python3 scripts/run.py --params '{}'

Call with Common Parameters

python3 scripts/run.py --params '{"riskFocus":"重点关注风险"}'

Parameter Description

Parameter	Type	Required	Default	Description
riskFocus	string	No	-	For example, overcommitment, missed requirements, compliance, delivery boundaries, competitor comparisons, or pricing statements
rfpContext	string	No	-	Supplement customer requirements, scoring rules, mandatory response items, procurement constraints, or clarification questions
reviewDepth	string	No	标准审阅	Review depth; optional values:快速风险摘要、标准审阅、深度响应改写
proposalFile	string	No	-	Supports proposal or bid documents such as docx, pdf, md, and txt
proposalText	string	No	-	Paste bid responses, pre-sales proposals, RFP answers, SOW drafts, or key sections
productContext	string	No	-	Describe product capabilities, delivery scope, cases, qualifications, pricing, dependency conditions, and boundaries that cannot be promised

For the complete machine-readable parameter structure, see references/form-schema.json。

Parameter Value Reference

The current skill has no categorical parameters that require additional table lookup.

Supported Input Formats

The current skill directly accepts JSON parameters and does not involve share link parsing.

Example Request

The example parameters below can be passed directly to scripts/run.py, and the runner will send them to the AI Skills API.

python3 scripts/run.py --params '{"riskFocus":"重点关注风险"}'

Equivalent --params JSON：

{
  "riskFocus": "重点关注风险"
}

Example Return Result

{
  "success": true,
  "data": {
    "message": "示例结果请以技能真实返回结构为准。"
  },
  "meta": {
    "executionTime": 842,
    "cached": false
  }
}

Delivery Content

• Summary, diagnostic conclusions, action recommendations, and reusable deliverables: organize the core results around the user's goals that can be directly read, reviewed, or delivered.
• Interpretation of input materials: extract key context and judgment basis by combining key risk concerns (for example, overcommitment, omitted requirements, compliance, delivery boundaries, competitor comparisons, or pricing statements.), RFP/customer requirement background (supplement customer requirements, scoring rules, mandatory response items, procurement constraints, or clarification questions.), and review depth (review depth).
• Next steps: provide priorities, execution recommendations, or a content framework that can be further developed.

Suggestions for Using the Results

• First determine whether the output answers the user's core questions about the "Risk Review Assistant".
• Then check whether the results cover the summary, diagnostic conclusions, action recommendations, and reusable deliverables, and whether clear next steps are provided.
• If there is little input material, it is recommended to have the user supplement the goals, audience, constraints, or source materials before running.

Preparation Before Running

• AISKILLS_BASE_URL: default https://ai-skills.ai
• AISKILLS_API_KEY: required, used for authenticated calls
• AISKILLS_TENANT_ID: default default