RRepoGEO

REPOGEO REPORT · LITE

openai/SWELancer-Benchmark

Default branch main · commit 4afbde31 · scanned 5/11/2026, 6:18:03 PM

GitHub: 1,441 stars · 138 forks

AI VISIBILITY SCORE
18 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
0 pass · 1 warn · 1 fail
Objective metadata checks
AI knows your name
2 / 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 openai/SWELancer-Benchmark, 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

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

OVERALL DIRECTION
  • highreadme#1
    Rewrite README to describe this repo's content and purpose

    Why:

    CURRENT
    # SWELancer
The SWE-Lancer codebase has been merged into https://github.com/openai/preparedness! 
**Please see https://github.com/openai/preparedness to run SWELancer**.
    COPY-PASTE FIX
    # SWELancer: Dataset and Code for LLM Software Engineering Benchmark

This repository contains the dataset and code for the paper "SWE-Lancer: Can Frontier LLMs Earn $1 Million from Real-World Freelance Software Engineering?". It provides a comprehensive benchmark for evaluating large language models on complex, end-to-end software engineering tasks that simulate real-world freelance jobs.

For the active codebase and to run SWELancer, please see the main project repository: https://github.com/openai/preparedness.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the repository root with a standard open-source license (e.g., MIT, Apache-2.0) that clarifies the terms of use for the dataset and code.

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 openai/SWELancer-Benchmark
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. CodeContests · recommended 2×
  3. MBPP · recommended 2×
  4. APPS · recommended 2×
  5. SWE-bench · recommended 1×
  • CATEGORY QUERY
    How to benchmark large language models on complex software development challenges?
    you: not recommended
    AI recommended (in order):
    1. SWE-bench
    2. HumanEval
    3. HumanEval-X
    4. MultiPL-E
    5. CodeContests
    6. BigCode Benchmarks
    7. MBPP
    8. APPS
    9. GitHub Actions
    10. GitLab CI/CD
    11. Jenkins
    12. Code Llama Benchmarks
    13. OpenAI Evals

    AI recommended 13 alternatives but never named openai/SWELancer-Benchmark. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What datasets exist for assessing AI performance in real-world coding projects?
    you: not recommended
    AI recommended (in order):
    1. HumanEval
    2. MBPP
    3. CodeContests
    4. APPS
    5. CodeXGLUE
    6. StarCoder Data
    7. LeetCode
    8. HackerRank

    AI recommended 8 alternatives but never named openai/SWELancer-Benchmark. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    Suggestion:

  • README presence
    warn

    Suggestion:

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 openai/SWELancer-Benchmark?
    pass
    AI did not name openai/SWELancer-Benchmark — likely talking about a different project

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

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

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

Embed your GEO score

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MARKDOWN (README)
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openai/SWELancer-Benchmark — 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