RRepoGEO

REPOGEO REPORT · LITE

NeoLabHQ/context-engineering-kit

Default branch master · commit dedca19c · scanned 5/27/2026, 12:12:03 PM

GitHub: 1,043 stars · 94 forks

AI VISIBILITY SCORE
33 /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
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 NeoLabHQ/context-engineering-kit, 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
    Clarify the README's introductory paragraph to emphasize 'marketplace of pre-built skills.'

    Why:

    CURRENT
    Hand-crafted collection of advanced context engineering techniques and patterns with minimal token footprint, focused on improving agent result quality and predictability. The marketplace is based on prompts used daily by our company developers for a long time, supplemented by plugins from benchmarked papers and high-quality projects.
    COPY-PASTE FIX
    The Context Engineering Kit is a hand-crafted marketplace of advanced context engineering techniques and patterns, offering pre-built, token-efficient skills focused on improving AI agent result quality and predictability. Unlike general LLM frameworks, CEK provides ready-to-use plugins based on battle-tested prompts and benchmarked research, designed for immediate integration into your AI assistant workflows.
  • mediumtopics#2
    Add more specific topics related to prompt engineering and AI agent skills.

    Why:

    CURRENT
    agent, ai, claude, cline, cursor, llm, marketplace, opencode, windsurf
    COPY-PASTE FIX
    agent, ai, claude, cline, cursor, llm, marketplace, opencode, windsurf, prompt-engineering, context-management, ai-skills, agent-skills, llm-prompts, prompt-library
  • lowreadme#3
    Add a dedicated section or clear statement on the core differentiator from LLM frameworks.

    Why:

    COPY-PASTE FIX
    ## Why Context Engineering Kit?
While general LLM frameworks (e.g., LangChain, LlamaIndex) provide foundational tools for building AI agents, the Context Engineering Kit offers a distinct advantage: a curated marketplace of *pre-built, token-efficient context engineering skills and patterns*. We focus on delivering immediate, measurable improvements to agent output quality and predictability, allowing developers to integrate proven techniques without reinventing the wheel.

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 NeoLabHQ/context-engineering-kit
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
langchain-ai/langchain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. langchain-ai/langchain · recommended 2×
  2. LangChain · recommended 1×
  3. LlamaIndex · recommended 1×
  4. Pinecone · recommended 1×
  5. Weaviate · recommended 1×
  • CATEGORY QUERY
    How can I improve AI agent code generation quality with advanced context engineering?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Pinecone
    4. Weaviate
    5. Chroma
    6. OpenAPI Specification
    7. JSON Schema
    8. Tree-sitter
    9. ANTLR
    10. GitHub Copilot
    11. Code Llama
    12. StarCoder
    13. AlphaCode

    AI recommended 13 alternatives but never named NeoLabHQ/context-engineering-kit. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking token-efficient prompt engineering skills for enhancing developer AI assistant output.
    you: not recommended
    AI recommended (in order):
    1. OpenAI Playground
    2. Anthropic Console
    3. LangChain (langchain-ai/langchain)
    4. Summarization Chains (langchain-ai/langchain)

    AI recommended 4 alternatives but never named NeoLabHQ/context-engineering-kit. 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 NeoLabHQ/context-engineering-kit?
    pass
    AI did not name NeoLabHQ/context-engineering-kit — 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 NeoLabHQ/context-engineering-kit in production, what risks or prerequisites should they evaluate first?
    pass
    AI named NeoLabHQ/context-engineering-kit 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 NeoLabHQ/context-engineering-kit solve, and who is the primary audience?
    pass
    AI named NeoLabHQ/context-engineering-kit explicitly

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

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