RRepoGEO

REPOGEO REPORT · LITE

mgechev/skills-best-practices

Default branch main · commit 979bd036 · scanned 5/22/2026, 8:57:41 AM

GitHub: 1,909 stars · 136 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 mgechev/skills-best-practices, 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 README's opening sentence to emphasize 'guide' nature

    Why:

    CURRENT
    This guide explains how to write professional-grade skills for agents, validate them using LLMs, and maintain a lean context window.
    COPY-PASTE FIX
    This repository provides a concentrated guide to best practices for creating agent skills, focusing on how to write, validate, and optimize them for LLM-powered applications.
  • hightopics#2
    Add relevant topics to improve categorization

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    agent-skills, llm-agents, best-practices, generative-ai, prompt-engineering, context-window-optimization, skill-development
  • mediumlicense#3
    Add a LICENSE file to clarify usage terms

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a LICENSE file in the root of the repository, choosing an appropriate open-source license (e.g., MIT, Apache-2.0) that aligns with your intentions for the project.

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 mgechev/skills-best-practices
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 1×
  2. LlamaIndex · recommended 1×
  3. Haystack · recommended 1×
  4. OpenAI Function Calling · recommended 1×
  5. Google Gemini's Function Calling · recommended 1×
  • CATEGORY QUERY
    How to structure and validate professional agent skills for LLM-powered applications?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. OpenAI Function Calling
    5. Google Gemini's Function Calling
    6. Pydantic
    7. Guardrails AI

    AI recommended 7 alternatives but never named mgechev/skills-best-practices. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are best practices for developing agent skills to optimize LLM context window usage?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LlamaIndex (run-llama/llama_index)
    3. Haystack (deepset-ai/haystack)
    4. Chroma (chroma-core/chroma)
    5. FAISS (facebookresearch/faiss)
    6. Pinecone
    7. Weaviate (weaviate/weaviate)
    8. OpenAI Function Calling API
    9. AutoGen (microsoft/autogen)

    AI recommended 9 alternatives but never named mgechev/skills-best-practices. 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 mgechev/skills-best-practices?
    pass
    AI did not name mgechev/skills-best-practices — 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 mgechev/skills-best-practices in production, what risks or prerequisites should they evaluate first?
    pass
    AI named mgechev/skills-best-practices 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 mgechev/skills-best-practices solve, and who is the primary audience?
    pass
    AI did not name mgechev/skills-best-practices — 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?

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mgechev/skills-best-practices — 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