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
86%
Does it follow best practices?
Impact
89%
1.45xAverage score across 13 eval scenarios
Advisory
Suggest reviewing before use
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.
Produce two files:
triage-report.md — the classification report in four sections.
dedup-output.json — the raw JSON output from the deduplication step.
evals
scenario-1
scenario-2
scenario-3
scenario-4
scenario-5
scenario-6
scenario-7
scenario-8
scenario-9
scenario-10
scenario-11
scenario-12
scenario-13
skills
batch-driver
build-and-evaluate
company-list-filter
discovery
discovery-produce
select-target