AiRecMark/Intelligence/Use case coverage
G-02 · Use case coveragearchive-recorded · snapshot 2026-09-17

Coding Use Cases & Weights

The recorded use-case layer of the coding category. Population: 55 archives in the Coding category, contributing 163 recorded entries and 139 distinct strings.

Key numbers

Archives in scope
55
data/tools · N=448
Recorded entries
163
finder.useCases[] · N=55
Tools with entries
55
finder.useCases · N=55
Distinct strings
139
finder.useCases[].useCase · N=163
Top string
Multi-file agentic edits (13)
frequency · N=163

Most frequent use-case strings

exact-string frequency within the scoped categories

#Use case (as recorded)EntriesAvg weight
1Multi-file agentic edits139
2Repository-aware context indexing138
3$5/mo included chat credits (Pro).18
410 AI Credits per 30 days with top-tier models.110
51M-token window on Pro.19
63-15 tasks in parallel by tier.19
7300+ models via one endpoint.110
845,000 orb-minutes/mo included on Individual.19
9Agentic coding across multiple repositories110
10Agentic coding with existing model subscriptions110
11Agentic feature development in large TS/C++ codebases19
12Agentic PR review with context-engine grounding.110

Weight distribution

w=61w=714w=848w=946w=1054

Recorded entry weights (1–10) within the scoped categories.

Method

  • Population: archives with category in [coding] (N=55); 163 recorded finder.useCases entries.
  • Frequency counts exact strings; average weight is the arithmetic mean of recorded weights rounded to 0.1.
  • No entries are synthesized for tools whose archives record none.
Data appendix. Source: data/tools/*.json · snapshot 2026-09-17 · method: useCase frequency/weight within category scope · aggregates published with method and N. T1 benchmarks recorded: 3 / 448.