Research and implementation landscape

The same techniques appear in research systems, skill packages, and BI products.

Read each row across: mechanism, strongest evidence, and limit stay aligned. Evidence grades are not product scores: A marks comparative human evidence, B a comparative benchmark, C an inspectable implementation, and D a product or author claim.

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System or package Mechanism Strongest evidence in this review Limit or missing evidence Source
A/CMixed initiative

Open-source tool + CHI paper

Data Formulator

Natural language for transformation; GUI for explicit encodings; visible tables, code, branches, and reversion.

Best signal Eight people reproduced 16 charts and 12 nontrivial transforms.

Supports authoring and verification behavior—not long-term analytical correctness.

Repository ↗
A/BScientific / 3D

Research prototype + preprint

Raiven

Metadata → RaivenDSL → deterministic compiler for linked 2D, 3D, and tabular views.

Best signal 100% compile and .988 VMPC on 100 fully specified prompts.

Most advantage is in SciVis; the task specifies the target view rather than discovering the question.

Paper ↗
BDashboard IR

Research architecture + preprint

NL2Dashboard

Compact IR separates analysis, content, and layout; atomic edits avoid full-dashboard rewrites.

Best signal Completed all edit tasks across seven modification classes with low output-token ratios.

Ten tables, LLM judge, unmatched model interfaces, and no user study.

Paper ↗
BDatabase visualization

Research system + ACL paper

nvAgent

Schema processor, sketch-and-fill VQL composer, and execution-guided validator.

Best signal +7.88 / +9.23 pass-rate points on single- / multi-table VisEval.

The composer drives most of the gain; processor value depends on model and environment.

Paper ↗
A/BRapid prototyping

Research prototype + preprint

DashChat

Pattern retrieval, a DSL, focused calls, chat plus structured edit bubbles, and visual history.

Best signal 100% executable and 94% spec consistency on 50 prompts; 28-person study.

Mock-data prototype tasks do not establish production analytics quality.

Paper ↗
CDeclarative agents

Open-source framework

Lumen

Coordinator routes to SQL, Vega-Lite, Deck.gl, source, table, and validation agents over serializable pipelines.

Best signal Inspectable implementation, deterministic profiling, and real capability boundaries.

No persuasive comparative efficacy study; one inspected validation path can fail open.

Repository ↗
C/DPrompt pipeline

Open-source research toolkit

LIDA

Summarization, persona-conditioned goals, chart-code generation, model scoring, repair, and recommendation.

Best signal Influential inspectable baseline for a modular prompt pipeline.

The evaluator does not inspect the final rendered image or create regression evidence.

Repository ↗
B−Multimodal feedback

Research method + preprint

PlotGen

Planner and code generator followed by numeric, lexical, and visual feedback agents.

Best signal 65.67 on MatPlotBench versus 61.16 and 48.86 baselines.

No equal-budget baseline; heavy VLM use and reporting inconsistencies obscure the causal mechanism.

Paper ↗
BAnalytic spec

Research method + preprint

NL4DV-LLM

Model emits an inspectable analytic specification and can preserve multiple interpretations of ambiguous prompts.

Best signal 87.02% across 740 queries versus 64.05% for rule-based NL4DV.

Older-model evidence; valid syntax does not guarantee correct binding.

Paper ↗
A/BEvaluation frontier

Benchmark + browser executor + judge

DashArena

Agent authors a dashboard and interaction trajectory; Playwright replays it; a calibrated judge sees task, schema, states, and execution evidence.

Best signal 234 tasks / 14 clusters; interaction evidence adds 8.1 points of human agreement.

Tableau-seed-biased, partial authored trajectories, and no reader-outcome measure.

Paper ↗
CEnd-to-end skill

Skill package inside an open-source tool

Vizro flow

Six staged skills, required specs and tests, AST checks, action enumeration, Playwright, and a test receipt.

Best signal Strongest mechanics of the skill packages inspected.

Seven fixtures and no aggregate held-out or independent human outcome.

Package ↗
CWorkflow skill

Agent skill package

OpenAI visualize-data

Question and takeaway first, explicit chart contract, data sufficiency, delivery routing, and final-context QA.

Best signal Broadest inspected contract and delivery checklist.

No behavioral comparison of an agent with and without the skill.

Skill ↗
CLibrary retrieval

Agent skills + reference corpus

AntV skills

Strict G2/G6/X6 version constraints plus hybrid retrieval over a large reference corpus.

Best signal Largest included retrieval and code benchmark in the inspected skills.

Saved runs did not include render results; “success” mostly means a response completed.

Package ↗
BScientific adapters

Skill family + paired evaluation

SciVisAgentSkills

Version-pinned guides for four scientific tool families, with headless execution and render–inspect–adjust loops.

Best signal Quality improved in all ten suite-by-agent comparisons across 108 tasks.

Author-built and author-evaluated, scientific tasks only; one completion measure fell and no independent or reader-outcome test was found.

Study ↗
C/DThin adapters

Two instruction-only skill packages

Vega + chart primers

Renderer syntax and examples in Markdown Viewer; long chart-literacy and accessibility prose in claude-skillz.

Best signal Useful surface adapters and a clean prompt-only baseline.

No fixtures, data checks, render loop, or outcome evaluation.

Vega skill ↗
DSemantic model

Commercial BI feature

Power BI Copilot

Selects tables, fields, measures, and charts from a semantic model; output remains editable in native tools.

Transfer Bind generation to governed measures and retain direct author control.

Current capability documentation, not comparative accuracy or user-outcome evidence.

Documentation ↗
DAuthoring state

Commercial BI feature

Tableau Agent

Uses connected-source fields, metadata, sample values, and worksheet state; results stay directly editable.

Transfer Keep agent scope close to native authoring state and make direct manipulation the recovery path.

The vendor says to review results and documents material current limitations.

Documentation ↗
DGoverned queries

Commercial BI feature

Looker Conversational Analytics

Grounds requests in LookML, permissions, descriptions, samples, glossaries, and optional verified queries.

Transfer Maintained semantic custody beats a generic analyst persona.

No public evidence here isolates which grounding feature improves decisions; outputs still require validation.

Documentation ↗

Skill-package maturity

One specialist family reaches paired proof; most packages do not.

  1. Adviceprose and examples
  2. Retrievalversioned references
  3. Artifactscontract and specs
  4. Checksdata and source
  5. Browserrender and actions
  6. Receiptsevidence retained
  7. Ablationwith / without skill
  8. Outcomehuman benefit

SciVisAgentSkills reaches paired ablation for specialized scientific work, but not independent reproduction or a human outcome. Vizro reaches furthest on execution evidence; AntV has the largest retrieval/code benchmark; OpenAI has the broadest contract and delivery QA. Those are different strengths—not one winner.

Public acquisition ≠ adoption

Every named row has an install signal. None exposes retained use.

Twelve listings collapse to ten parent repositories and eleven documented lineages. The listing fields sum to 37,720, but that is not a people, team, successful-install, invocation, or outcome count.

12/12listed

12/12install signal

0/12invocation

0/12retention · organization · outcome

  1. Listedstable listing
  2. Install signalregistry field
  3. Presenceexact version
  4. Invocationreal task
  5. Retentionreturn use
  6. Acceptancenamed owner
  7. Outcomelater recheck

The 0/12 values mean “not observed on these named public surfaces,” not “nobody uses the package.” Use installs to decide what to inspect. Require later receipts before claiming adoption, procurement value, or effectiveness.

Controls ≠ governed deployment

Two real evidence rails. Zero complete joins.

Three provider families expose controls; two provider stories report named-feature organizational use; two studies add adjacent governance practice. None carries the complete same-deployment record.

Rail 01 · available controls 3

Power BI · Tableau · Looker

Enablement, data or semantic boundaries, and monitoring surfaces an organization can configure.

0 / 7 complete rows
Rail 02 · reported use 2

Google Cloud Support · KPMG

Provider-published reports of named-feature organizational use, without the complete control and outcome record.

  1. 01Feature + version
  2. 02Authorization
  3. 03Scope
  4. 04Data authority
  5. 05Audit
  6. 06Routine use
  7. 07Incident
  8. 08Accepted outcome
  9. 09Later recheck

All nine receipts must meet on one feature-specific deployment row. Do not splice provider controls to another customer's reported outcome. The zero is bounded to seven held public rows; stronger private records remain unknown.