RRepoGEO

REPOGEO REPORT · LITE

YennNing/Awesome-Code-as-Agent-Harness-Papers

Default branch main · commit 06b0d447 · scanned 6/28/2026, 4:02:55 PM

GitHub: 519 stars · 40 forks

AI VISIBILITY SCORE
22 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 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 YennNing/Awesome-Code-as-Agent-Harness-Papers, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    awesome-list, research-papers, ai-agents, code-as-agent, generative-ai, llm-agents, machine-learning, survey, agentic-ai
  • highreadme#2
    Clarify the repository's type as a curated list in the README's opening

    Why:

    CURRENT
    # Awesome Code as Agent Harness Papers

This repository accompanies the survey **Code as Agent Harness: Toward Executable, Verifiable, and Stateful Agent Systems**.
    COPY-PASTE FIX
    # Awesome Code as Agent Harness Papers

This is a curated list of research papers and resources, accompanying the survey **Code as Agent Harness: Toward Executable, Verifiable, and Stateful Agent Systems**.
  • mediumhomepage#3
    Add the survey's official webpage as the repository homepage

    Why:

    COPY-PASTE FIX
    https://code-as-harness.github.io/code-as-harness-webpage/

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 YennNing/Awesome-Code-as-Agent-Harness-Papers
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
XState
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. XState · recommended 1×
  2. SCXML · recommended 1×
  3. BehaviorTree.CPP · recommended 1×
  4. py_trees · recommended 1×
  5. Gymnasium · recommended 1×
  • CATEGORY QUERY
    How to design AI agents with executable, verifiable, and stateful control mechanisms?
    you: not recommended
    AI recommended (in order):
    1. XState
    2. SCXML
    3. BehaviorTree.CPP
    4. py_trees
    5. Gymnasium
    6. Stable Baselines3
    7. Ray RLlib
    8. Prolog
    9. Datalog
    10. RxJS
    11. Akka Streams

    AI recommended 11 alternatives but never named YennNing/Awesome-Code-as-Agent-Harness-Papers. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find research on using code to build robust and inspectable AI agent systems?
    you: not recommended
    AI recommended (in order):
    1. arXiv.org
    2. Google Scholar
    3. ACL Anthology
    4. NeurIPS
    5. ICML
    6. ICLR
    7. PMLR (Proceedings of Machine Learning Research)
    8. AAAI
    9. IJCAI
    10. ACM Digital Library
    11. IEEE Xplore
    12. Journal of Artificial Intelligence Research (JAIR)

    AI recommended 12 alternatives but never named YennNing/Awesome-Code-as-Agent-Harness-Papers. This is the gap to close.

    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 YennNing/Awesome-Code-as-Agent-Harness-Papers?
    pass
    AI did not name YennNing/Awesome-Code-as-Agent-Harness-Papers — 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 YennNing/Awesome-Code-as-Agent-Harness-Papers in production, what risks or prerequisites should they evaluate first?
    pass
    AI named YennNing/Awesome-Code-as-Agent-Harness-Papers 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 YennNing/Awesome-Code-as-Agent-Harness-Papers solve, and who is the primary audience?
    pass
    AI did not name YennNing/Awesome-Code-as-Agent-Harness-Papers — 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 YennNing/Awesome-Code-as-Agent-Harness-Papers. 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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YennNing/Awesome-Code-as-Agent-Harness-Papers — 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