RRepoGEO

REPOGEO REPORT · LITE

SWE-bench/SWE-smith

Default branch main · commit 9b74ac08 · scanned 6/5/2026, 11:27:40 AM

GitHub: 668 stars · 120 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
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 SWE-bench/SWE-smith, 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
    Reposition the core value proposition to the top of the README

    Why:

    CURRENT
    The README's first descriptive text is "SWE-smith is a toolkit for training SWE-agents." appearing after badges and a spotlight.
    COPY-PASTE FIX
    SWE-smith is a comprehensive toolkit designed for **generating large-scale, real-world software engineering tasks from any GitHub repository** to **train and evaluate AI agents (SWE-agents)**. It enables the creation of unlimited tasks like file localization and program repair, and facilitates the training of language models to become better software engineers.
  • hightopics#2
    Add more specific topics to reinforce the repo's category

    Why:

    CURRENT
    agents, language-model, software-engineering, training
    COPY-PASTE FIX
    agents, language-model, software-engineering, training, dataset-generation, llm-evaluation, code-repair, ai-agents, software-agents, benchmarking
  • mediumabout#3
    Refine the 'About' description for clarity on purpose

    Why:

    CURRENT
    [NeurIPS 2025 D&B Spotlight] Scaling Data for SWE-agents
    COPY-PASTE FIX
    A toolkit for generating large-scale, real-world software engineering tasks from GitHub repositories to train and evaluate AI agents.

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
0 / 2
0% of queries surface SWE-bench/SWE-smith
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
HumanEval
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. HumanEval · recommended 2×
  2. Codeforces · recommended 2×
  3. LeetCode · recommended 2×
  4. AtCoder · recommended 1×
  5. Google Code Jam · recommended 1×
  • CATEGORY QUERY
    Seeking a platform to train and evaluate AI agents on real-world coding challenges.
    you: not recommended
    AI recommended (in order):
    1. HumanEval
    2. Codeforces
    3. AtCoder
    4. LeetCode
    5. Google Code Jam
    6. Meta Hacker Cup
    7. Codewars
    8. DeepMind's AlphaCode Problems

    AI recommended 8 alternatives but never named SWE-bench/SWE-smith. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to generate large-scale datasets for evaluating AI coding assistants?
    you: not recommended
    AI recommended (in order):
    1. HumanEval
    2. MBPP
    3. APPS
    4. Codeforces
    5. LeetCode
    6. GitHub
    7. GitLab
    8. CodeSearchNet
    9. American Fuzzy Lop (AFL)
    10. libFuzzer
    11. GPT-4
    12. Claude 3
    13. ANTLR
    14. Xtext
    15. Amazon Mechanical Turk
    16. Upwork
    17. Appen

    AI recommended 17 alternatives but never named SWE-bench/SWE-smith. This is the gap to close.

    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 SWE-bench/SWE-smith?
    pass
    AI named SWE-bench/SWE-smith explicitly

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

  • If a team adopts SWE-bench/SWE-smith in production, what risks or prerequisites should they evaluate first?
    pass
    AI named SWE-bench/SWE-smith 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 SWE-bench/SWE-smith solve, and who is the primary audience?
    pass
    AI named SWE-bench/SWE-smith explicitly

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

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SWE-bench/SWE-smith — 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