Score RFP opportunities with a six-dimension framework and eligibility gate.
npx skills add https://github.com/Atemndobs/nebula-rfp --skill rfp-evaluate
Please help me install this Agent Skill. Skill: rfp-evaluate Source: https://github.com/Atemndobs/nebula-rfp/tree/main/.claude/skills/rfp-evaluate Command: npx skills add https://github.com/Atemndobs/nebula-rfp --skill rfp-evaluate
This skill standardizes the evaluation of RFP opportunities by applying a structured six-dimension scoring framework, ensuring consistent decisions across teams.
Provide a new RFP opportunity to the evaluation engine; the system will apply eligibility checks, compute the six-dimension score, and return a decision.
High-intent search queries and answers about installing and using this skill.
RFP scoring applies a predefined eligibility gate to categorize opportunities as eligible, needs_partner, or rejected. It then uses a six-dimension framework to compute a 0-100 score, generating a pass/fail decision and governance recommendation.
The best way to standardize vendor selection is applying a weighted six-dimension framework covering Technical Relevance, Scope Fit, Category Focus, Client Profile, Logistics, and Skill Alignment to generate consistent 0-100 scores and structured pass/fail decisions.
You can evaluate RFP opportunities by applying hard eligibility filters and scoring criteria. The system generates a per-criterion breakdown, matched keywords, and a final recommendation of pursue, maybe, or skip suitable for governance.
You can configure criteria by defining specific keywords, weights, and minMatches for precise control over RFP scoring. This ensures the six-dimension assessment accurately reflects your governance requirements and vendor selection standards.
If an RFP opportunity fails the eligibility gate, it is categorized as rejected or needs_partner to prevent wasted proposals. This hard filter stops low-quality opportunities before the six-dimension scoring framework is applied.
The RFP evaluation framework supports optional AI analysis to augment keyword matching and semantic alignment with criteria. This AI-augmented evaluation enhances the accuracy of the six-dimension scoring and final governance recommendation.
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