RRepoGEO

REPOGEO REPORT · LITE

openai/following-instructions-human-feedback

Default branch main · commit 5c0534c7 · scanned 6/21/2026, 10:38:15 PM

GitHub: 1,259 stars · 148 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
17 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
1 / 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/following-instructions-human-feedback, 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
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    Official code and resources for the InstructGPT paper: 'Training Language Models to Follow Instructions with Human Feedback' using Reinforcement Learning from Human Feedback (RLHF).
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a LICENSE file in the repository root. If the intent is a permissive license for research, consider adding an MIT or Apache-2.0 license. If it's for non-commercial research use, specify that clearly.

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/following-instructions-human-feedback
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI API
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI API · recommended 1×
  2. Hugging Face Transformers library · recommended 1×
  3. TRL library · recommended 1×
  4. LangChain · recommended 1×
  5. LlamaIndex · recommended 1×
  • CATEGORY QUERY
    How can I make my large language model more aligned with user intent and helpful?
    you: not recommended
    AI recommended (in order):
    1. OpenAI API
    2. Hugging Face Transformers library
    3. TRL library
    4. LangChain
    5. LlamaIndex
    6. Pinecone
    7. Weaviate
    8. ChromaDB
    9. Weights & Biases Prompts
    10. Helicone
    11. Label Studio
    12. Argilla

    AI recommended 12 alternatives but never named openai/following-instructions-human-feedback. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What techniques exist for improving language model output quality through human feedback?
    you: not recommended
    AI recommended (in order):
    1. Proximal Policy Optimization (PPO)
    2. Direct Preference Optimization (DPO)
    3. Constitutional AI (CAI)
    4. Alpaca-LoRA (tloen/alpaca-lora)
    5. OpenAssistant Conversations Dataset (OASST1) (LAION-AI/Open-Assistant)
    6. Argilla (argilla-io/argilla)
    7. Snorkel (snorkel-team/snorkel)

    AI recommended 7 alternatives but never named openai/following-instructions-human-feedback. 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
    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 openai/following-instructions-human-feedback?
    pass
    AI did not name openai/following-instructions-human-feedback — 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/following-instructions-human-feedback in production, what risks or prerequisites should they evaluate first?
    pass
    AI named openai/following-instructions-human-feedback 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/following-instructions-human-feedback solve, and who is the primary audience?
    pass
    AI did not name openai/following-instructions-human-feedback — 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?

Embed your GEO score

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

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/openai/following-instructions-human-feedback.svg)](https://repogeo.com/en/r/openai/following-instructions-human-feedback)
HTML
<a href="https://repogeo.com/en/r/openai/following-instructions-human-feedback"><img src="https://repogeo.com/badge/openai/following-instructions-human-feedback.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

openai/following-instructions-human-feedback — 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