RRepoGEO

REPOGEO REPORT · LITE

yizhongw/self-instruct

Default branch main · commit 0b26ccaa · scanned 5/9/2026, 3:27:56 PM

GitHub: 4,598 stars · 524 forks

AI VISIBILITY SCORE
69 /100
Needs work
Category recall
1 / 2
Avg rank #1.0 when recommended
Rule findings
1 pass · 1 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 yizhongw/self-instruct, 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
    Strengthen README's opening to highlight self-generation as the solution to manual annotation

    Why:

    CURRENT
    This repository contains code and data for the Self-Instruct paper, a method for aligning pretrained language models with instructions.
    COPY-PASTE FIX
    This repository contains code and data for Self-Instruct, a novel method that enables language models to *self-generate* their own instruction-following data, drastically reducing the need for extensive and costly manual annotation.
  • mediumtopics#2
    Add more specific topics related to synthetic data generation

    Why:

    CURRENT
    general-purpose-model, instruction-tuning, language-model
    COPY-PASTE FIX
    general-purpose-model, instruction-tuning, language-model, synthetic-data-generation, llm-data-generation, instruction-data-bootstrapping
  • lowhomepage#3
    Add the official paper URL as the repository homepage

    Why:

    COPY-PASTE FIX
    https://arxiv.org/abs/2212.10560

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
1 / 2
50% of queries surface yizhongw/self-instruct
Avg rank
#1.0
Lower is better. #1 = top recommendation.
Share of voice
6%
Of all named tools, what % are you?
Top rival
Alpaca
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Alpaca · recommended 1×
  2. GPT-3.5 Turbo · recommended 1×
  3. GPT-4 · recommended 1×
  4. LoRA · recommended 1×
  5. Hugging Face PEFT · recommended 1×
  • CATEGORY QUERY
    How can I improve language model instruction following without extensive manual data annotation?
    you: not recommended
    AI recommended (in order):
    1. Alpaca
    2. GPT-3.5 Turbo
    3. GPT-4
    4. LoRA
    5. Hugging Face PEFT
    6. Argilla
    7. Label Studio

    AI recommended 7 alternatives but never named yizhongw/self-instruct. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools exist for automatically generating instruction-following data for large language models?
    you: #1
    AI recommended (in order):
    1. Self-Instruct ← you
    2. AlpacaFarm (stanford-crfm/alpaca_farm)
    3. ShareGPT.com
    4. ShareGPT-90K
    5. OpenAssistant Conversations Dataset (OASST1)
    6. Hugging Face TRL (Transformer Reinforcement Learning) (huggingface/trl)
    7. DeepSpeed-Chat (microsoft/DeepSpeedExamples)
    8. LangChain (langchain-ai/langchain)
    9. LlamaIndex (run-llama/llama_index)
    Show full AI answer

Objective checks

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

  • Metadata completeness
    warn

    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 yizhongw/self-instruct?
    pass
    AI named yizhongw/self-instruct explicitly

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

  • If a team adopts yizhongw/self-instruct in production, what risks or prerequisites should they evaluate first?
    pass
    AI named yizhongw/self-instruct 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 yizhongw/self-instruct solve, and who is the primary audience?
    pass
    AI named yizhongw/self-instruct 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 yizhongw/self-instruct. 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/yizhongw/self-instruct.svg)](https://repogeo.com/en/r/yizhongw/self-instruct)
HTML
<a href="https://repogeo.com/en/r/yizhongw/self-instruct"><img src="https://repogeo.com/badge/yizhongw/self-instruct.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

yizhongw/self-instruct — 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