RRepoGEO

REPOGEO REPORT · LITE

ropensci/drake

Default branch main · commit 48324887 · scanned 6/30/2026, 9:21:54 PM

GitHub: 1,340 stars · 130 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
89 /100
Healthy
Category recall
2 / 2
Avg rank #2.0 when recommended
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface ropensci/drake, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Ensure README starts with a clear, concise project description

    Why:

    CURRENT
    <center>

</center>
<table class="table">
<thead>
<tr class="header">
<th align="left">
Usage
</th>
<th align="left">
Release
</th>
<th align="left">
Development
</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td align="left">
<a href="https://www.gnu.org/licenses/gpl-3.0.en.html"></a>
</td>
<td align="left">
<a href="https://cran.r-project.org/package=drake"></a>
</td>
<td align="left">
<a href="https://github.com/ropensci/drake/actions?query=workflow%3Acheck"></a>
</td>
</tr>
<tr class="even">
<td align="left">
<a href="https://cran.r-project.org/"></a>
</td>
<td align="left">
<a href="https://cran.r-project.org/web/checks/check_results_drake.html"></a>
</td>
<td align="left">
<a href="https://github.com/ropensci/drake/actions?query=workflow%3Alint"></a>
</td>
</tr>
<tr class="odd">
<td align="left">
<a href="https://CRAN.R-project.org/package=drake"></a>
</td>
<td align="left">
<a href="https://github.com/ropensci/software-review/issues/156"></a>
</td>
</tr>
<tr class="even">
<td align="left">
<a href="https://CRAN.R-project.org/package=drake"></a>
</td>
<td align="left">
<a href="https://doi.org/10.21105/joss.00550"></a>
</td>
<td align="left">
<a href="https://bestpractices.coreinfrastructure.org/projects/2135"></a>
</td>
</tr>
<tr class="odd">
<td align="left">
</td>
<td align="left">
<a href="https://zenodo.org/badge/latestdoi/82609103"></a>
</td>
<td align="left">
<a href="https://lifecycle.r-lib.org/articles/stages.html"></a>
</td>
</tr>
</tbody>
</table>
<br>

# drak
    COPY-PASTE FIX
    The `drake` R package is a pipeline toolkit for reproducibility and high-performance computing, designed to manage complex data analysis workflows by intelligently re-running only necessary steps.
  • mediumcomparison#2
    Add a comparison section to clarify `drake`'s niche

    Why:

    COPY-PASTE FIX
    ## Comparison to other R tools

`drake` is a workflow management system, distinct from general R packages for environment management (like `renv`), report generation (like `R Markdown`), or file path handling (like `here`). It focuses specifically on building and managing reproducible data analysis pipelines, similar in scope to its successor, `targets`.
  • lowtopics#3
    Add more specific data pipeline and workflow orchestration topics

    Why:

    CURRENT
    data-science, drake, high-performance-computing, makefile, peer-reviewed, pipeline, r, r-package, reproducibility, reproducible-research, ropensci, rstats, workflow
    COPY-PASTE FIX
    data-science, drake, high-performance-computing, makefile, peer-reviewed, pipeline, r, r-package, reproducibility, reproducible-research, ropensci, rstats, workflow, data-pipeline, workflow-orchestration, data-engineering

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
2 / 2
100% of queries surface ropensci/drake
Avg rank
#2.0
Lower is better. #1 = top recommendation.
Share of voice
13%
Of all named tools, what % are you?
Top rival
r-lib/targets
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. r-lib/targets · recommended 1×
  2. rstudio/renv · recommended 1×
  3. rstudio/rmarkdown · recommended 1×
  4. r-lib/here · recommended 1×
  5. r-lib/testthat · recommended 1×
  • CATEGORY QUERY
    What R packages help build robust, reproducible data analysis pipelines?
    you: #2
    AI recommended (in order):
    1. targets (r-lib/targets)
    2. drake (ropensci/drake) ← you
    3. renv (rstudio/renv)
    4. R Markdown (rstudio/rmarkdown)
    5. here (r-lib/here)
    6. testthat (r-lib/testthat)
    7. Docker
    8. containerit (o2r/containerit)
    9. rocker (rocker-org/rocker)
    Show full AI answer
  • CATEGORY QUERY
    Seeking an R workflow manager for high-performance computing and complex data tasks.
    you: #2
    AI recommended (in order):
    1. targets
    2. drake ← you
    3. snakemake
    4. Nextflow
    5. MakeR
    6. workflowr
    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of ropensci/drake?
    pass
    AI named ropensci/drake explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts ropensci/drake in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ropensci/drake explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo ropensci/drake solve, and who is the primary audience?
    pass
    AI named ropensci/drake explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of ropensci/drake. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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ropensci/drake — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite