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jbaruch/auto-skill-discovery

Automated pipeline that takes a company name and produces a custom Tessl skill plus an eval report showing per-scenario lift (baseline agent vs with-skill agent). A1 MVP cell of the produce/consume × personalization 2x2.

88

1.45x
Quality

86%

Does it follow best practices?

Impact

89%

1.45x

Average score across 13 eval scenarios

SecuritybySnyk

Advisory

Suggest reviewing before use

Overview
Quality
Evals
Security
Files

task.mdevals/scenario-8/

Pre-Discovery Prioritization for an Industry Summit

Problem/Feature Description

Your company is attending a European tech summit and has assembled a list of 16 companies from the sponsor and speaker roster. Before investing discovery pipeline time on each one, you need a fast triage pass that separates the obviously-useful leads from the structural dead-ends.

A key challenge with this list is that several of the names look like coherent single companies but may actually be multi-brand holding structures where a sub-brand specifier would be required before discovery can produce a coherent result. At the same time, the list also includes financial-sector and consulting-sector companies that your discovery pipeline handles fine — you don't want to inadvertently drop those just because of their sector.

Produce a triage report for this list. The raw names are at inputs/companies.txt.

Output Specification

Produce two files:

  1. triage-report.md — the classification report in four sections.

  2. dedup-output.json — the raw JSON output from the deduplication step.

evals

discovery-output-contract.md

README.md

tile.json