Score candidate lists on Scale, Cost, and Quality with evidence.
npx skills add https://github.com/kamilseghrouchni/vcro-sourcing --skill query-score
Please help me install this Agent Skill. Skill: query-score Source: https://github.com/kamilseghrouchni/vcro-sourcing/tree/main/.claude/skills/query/score Command: npx skills add https://github.com/kamilseghrouchni/vcro-sourcing --skill query-score
This skill enables transparent, multi-axis scoring of candidate lists, preventing opaque rankings and ensuring traceable evidence for each candidate.
candidates.json, wiki entity articles, and pricing references to generate per-axis evidence and avoid hidden biases.Run the scoring process on a given candidates.json to produce scored_candidates.json with three axes and evidence per candidate.
High-intent search queries and answers about installing and using this skill.
Tri-axis candidate scoring evaluates data candidates across Scale, Cost, and Quality by reading candidates.json, wiki articles, and pricing references. It generates scored_candidates.json with per-axis evidence and a citeable provenance trail to prevent opaque rankings.
Run the scoring process on a candidates.json file. The skill cross-references wiki entity articles and pricing references to produce scored_candidates.json, containing per-axis evidence, axis_confidences, and a detailed provenance trail for each candidate.
Yes, a broker can use candidates.json with wiki entity articles and pricing references to evaluate multiple candidates for a procurement task. This presents buyers with three scored axes to tailor weighting for data availability and cost estimates.
To ensure traceable evidence in candidate sourcing, use a multi-axis scoring skill that generates a citeable provenance trail. It outputs scored_candidates.json with explicit per-axis evidence and axis_confidences, avoiding hidden biases in candidate rankings.
Yes, pricing references are required alongside candidates.json and wiki entity articles to accurately assess the Cost axis. This inputs allow the scoring process to generate cost estimates and compare data availability with explicit evidence.
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