AutoQA Foundation - The Question Inventory
The decision-gating questions that define what the system must measure, automate, escalate, and govern.
Search or pick a category. Then open the file or download the original.
The download is the original file.
The full-text index and the search index are JSON files, with sizes and checksums.
The foundation package and the miniqa bundle are the downloads. Each one lists its format, size, and checksum. Raw downloads the original file.
The full-text index is the file search uses for file contents.
These are working drafts. Names and file paths in them may be out of date.
Published judge studies mostly score model output, not a person's written evaluation. Positive praise still has to be checked on your own work.
The decision-gating questions that define what the system must measure, automate, escalate, and govern.
Executive synthesis of the recency-biased research sweep, including strongest findings, disagreements, caveats, and gaps.
The eleven principles, eight-stage architecture, operating model, legal floor, and unresolved decisions.
The full 92-question brainstorm across measurement, judge failure modes, rubric operations, human factors, grounding, workflow, and feedback.
All domain reports concatenated into one source atlas, with evidence summaries, tools, disagreements, gaps, and verification notes.
Adversarial audit of the original sweep, plus psychometrics, legal, content moderation, and feedback-science gap fills.
Academic judge benchmarks, task-dependent capability limits, bias, and model-selection evidence.
Annotation disagreement, rater uncertainty, LLM contamination, label error, and human-assistance effects.
CriticGPT lineage, human-plus-critic evidence, omission limits, and feedback validation.
Claim verification, evidence closure, decomposition, citation quality, and faithfulness detectors.
Prediction-powered inference, selective escalation, conformal routing, calibration, and drift attribution.
Rubric compilation, criterion-level grading, rubric failure modes, and expert-grounded exemplars.
Production QA stacks, reviewer trust telemetry, vendor calibration patterns, and verifier economics.
The strongest case against naive AutoQA: invalidity, gaming, correlated errors, automation bias, and limits.
The newest verifier, routing, rubric, and judge findings through early July 2026.
How to construct adjudicated gold data, calibrate evaluators, run ablations, set launch gates, and monitor drift.
Version history and recorded changes for the foundation package.
Normative semantics for project contracts, evidence, criteria, findings, uncertainty, feedback, security, and conformance.
A target-specific rule engine for accept, rework, reject, and escalate decisions, including the bounded human interaction.
Machine-readable inventory and hashes for the complete package.
Package overview, core model, invariants, adoption sequence, and conformance levels.
Current package version identifier.
Adjudicated benchmark record for the synthetic case, including acceptable outcomes and ambiguity metadata.
A strong attempt incorrectly failed by a human reviewer for not forcing an unsupported binary conclusion.
Complete AutoQA result accepting the attempt, returning the annotation for rework, and generating audience-specific feedback.
A bounded precedence question that hides the provisional decision and asks only what can change the outcome.
Synthetic closed-world evidence project with positive-proof requirements, anchors, severity, and explicit decision rules.
Runtime schema for adjudicated truth, acceptable actions, ambiguity, challenge attributes, and leakage controls.
Runtime schema for task, evidence bundle, attempt, human review, references, and provenance.
Shared runtime definitions used by the project, case, evaluation, benchmark, and resolution schemas.
Runtime schema for claims, evidence relationships, findings, criterion assessments, decisions, annotation audit, and feedback.
Runtime schema for one bounded, decision-changing human question and its context.
Runtime schema for approved project instructions, criteria, evidence policy, decision policy, and calibration requirements.
CSV template for drafting criterion intent, proof standards, failure anchors, evidence requirements, severity, and governance.
CSV template for building an adjudicated calibration and test set.
CSV template for comparing evaluator configurations by criterion family.
Strict TypeScript types for project contracts, cases, evaluations, benchmarks, findings, decisions, feedback, and human resolution.
Compiler configuration for the package's type definitions.
Canonical content hashing utilities used by the validation suite.
Python validator for the package's example documents.
Cross-document, schema, hash, proof-invariant, policy, and package integrity checks.
| File | Format | Size | SHA-256 |
|---|---|---|---|
| autoqa-foundation-v0.1.0.zip | ZIP | 78.3 KB | e020f1e46f91 |
| miniqa-0.2.0-20260717.zip | ZIP | 29.2 KB | 790381cacf9b |
| File | Format | Size | SHA-256 |
|---|---|---|---|
| assets/library-fulltext.json | JSON | 1.0 MB | df3ce0d313f7 |
| assets/search-index.json | JSON | 718.8 KB | 7abf9be3f146 |
Source: site/library.html