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Coverage Stories

Organize benchmark coverage intent into governed Stories and testable facet tuples.

Coverage Stories

Prerequisites

  • Ready coverage setup or a clearly justified manual Story.
  • Coverage Facets that can name the intended behavior slice.

A Coverage Story turns benchmark intent into a coherent behavior slice. It explains what matters, why it matters, and which facet combinations must be exercised without pretending that a chart category alone describes a real product situation.

Stories can be created manually or proposed by generation. Their lifecycle is draft, active, or archived, and their origin remains visible as AI-generated or manual. A Story contains a title, description, rationale, intent, budget, referenced facets, suggested Topic Groups, and one or more tuples.

Make tuples testable

Each tuple names a smaller test obligation through its title, must_prove statement, facet references, target, accepted count, status, and flags. Write must_prove so Case Review can decide whether a candidate actually supplies the required evidence. Avoid vague goals such as “good edge cases.” Name the actor, conflict, evidence, constraint, or transformation that distinguishes the tuple.

Targets express desired evidence volume; accepted counts report materialized evidence. Neither number proves quality. A tuple can meet its count while still containing redundant or unrealistic Cases, so review remains mandatory.

Edit and govern the Story map

Use the editor to create or revise a Story and add, edit, or remove tuples. Archive a Story whose behavior is no longer in benchmark scope. Do not delete or rewrite the rationale merely because the current dataset already covers it; that rationale explains why the evidence exists.

When generation is running, partial, failed, or based on changed setup, read the displayed generation state before acting. A generated Story remains a proposal until the saved story and tuple structure reflects the benchmark intent.

Worked example

Example: superseded-source conflict

A Story covers answers that cite a plausible but superseded policy. One tuple must prove that the candidate detects the date conflict; another must prove that it asks for clarification when the current source is incomplete. Their separate targets prevent several near-duplicate date cases from masquerading as coverage of both behaviors.

Object and state changes

Creating or editing changes the saved Story and tuple map. Archiving removes a Story from active planning while preserving it. Generation can propose Stories but does not accept Cases into the dataset.

Success criteria

  • Every active Story has a clear rationale and testable tuples.
  • Targets and accepted counts remain distinguishable.
  • Story origin and generation freshness are visible.

Common failure modes

  • Writing tuples that cannot be judged in Case Review.
  • Treating target count as evidence quality.
  • Merging distinct Topic or facet obligations into vague coverage prose.

Related reference pages

Concept / Coverage ManagementCoverage ManagementManage benchmark coverage from setup through representation, Coverage Stories, case review, Case Foundry, and contribution requests.Reference / Coverage EngineeringProject TopicsMaintain source-grounded subject areas, editable groups, and Atlas relationships used to organize project and benchmark coverage.Reference / Coverage EngineeringCase Construction PatternsDefine reusable mechanisms for constructing cases and steer how benchmarks use or avoid them.

Related troubleshooting pages

Troubleshooting / Recovery LibraryUnbalanced CoverageFix benchmarks that overrepresent easy or common cases while missing important behavior.Troubleshooting / Recovery LibraryStale DimensionsRefresh Dimensions and ontology values that no longer explain the current behavior space without rewriting historical evidence.

Source confidence

Code-backed: the current Coverage Stories page, editor, and types define Story origin, lifecycle, fields, tuple structure, counts, and generation presentation.

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Related docs

Coverage Management Coverage Management Manage benchmark coverage from setup through representation, Coverage Stories, case review, Case Foundry, and contribution requests. Coverage Management Set Up Benchmark Coverage Define benchmark intent, facet handling, artifact preferences, and evidence requirements before generating coverage work. Coverage Management Case Foundry Generate or update bounded case candidates from the saved coverage setup and Story map. Coverage Management Case Review Prepare, inspect, refine, and admit Case candidates and generated materials into the benchmark dataset.
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