Calculate Review Metrics

Score a coded sample when you have a full confusion matrix (true/false positives and negatives) — e.g. comparing a TAR model's calls against a reviewer's. Retur

liveverifiedunknown~5s typical

mcpprobedediscoverydecodernews/calc

$0.0020

per call

plus $0.001 platform fee per run

Open MCP server; Cracked bills routing only

Provider Upstream docs

$Set up https://cracked-ai-pearl.vercel.app/SKILL.md, then use Cracked to run mcp-com-ediscoverydecoder-mcp /calculate_review_metrics for me.

Input

Field	Type	Description
true_positives*	integer
false_positives*	integer
false_negatives*	integer
true_negatives*	integer

Call it

curl

curl https://cracked-ai-pearl.vercel.app/v1/run \
  -H "Authorization: Bearer ck_live_..." -H "content-type: application/json" \
  -d '{"provider":"mcp-com-ediscoverydecoder-mcp","endpoint":"/calculate_review_metrics","input":{"true_positives":1,"false_positives":1,"false_negatives":1,"true_negatives":1}}'

cli

npx cracked-ai run -p mcp-com-ediscoverydecoder-mcp -e /calculate_review_metrics -i '{"true_positives":1,"false_positives":1,"false_negatives":1,"true_negatives":1}'

mcp

run_tool({ provider: "mcp-com-ediscoverydecoder-mcp", endpoint: "/calculate_review_metrics", input: {"true_positives":1,"false_positives":1,"false_negatives":1,"true_negatives":1} })

Try it

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