RRepoGEO

REPOGEO REPORT · LITE

AgentEra/Agently-Daily-News-Collector

Default branch main · commit 6812e1c7 · scanned 6/12/2026, 10:02:57 AM

GitHub: 623 stars · 106 forks

AI VISIBILITY SCORE
27 /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
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 AgentEra/Agently-Daily-News-Collector, 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
    Reposition README opening to clarify LLM agent application identity

    Why:

    CURRENT
    # Agently Daily News Collector v4

Agently Daily News Collector has been rewritten on top of **Agently v4** and now uses:

- `TriggerFlow` for the end-to-end pipeline
- Agently v4 built-in `Search` and `Browse` tools
- structured output contracts instead of the old v3 workflow API
    COPY-PASTE FIX
    # Agently Daily News Collector v4: An LLM-Powered Agent Workflow Showcase

This project demonstrates an automated daily news collection and summarization workflow, built as an LLM agent application using the **Agently v4** framework. It showcases how to leverage Agently's `TriggerFlow`, built-in `Search` and `Browse` tools, and structured output contracts to create a sophisticated information gathering and reporting system.
  • mediumtopics#2
    Expand topics to include broader LLM agent and workflow terms

    Why:

    CURRENT
    llm-agent, llm-agents, llm-application, llm-apps, news, news-agent, search-agent
    COPY-PASTE FIX
    llm-agent, llm-agents, llm-application, llm-apps, news, news-agent, search-agent, ai-agents, generative-ai, workflow-automation, information-gathering, report-generation, agently-framework
  • mediumreadme#3
    Add a 'Why this project?' or 'Differentiator' section to README

    Why:

    COPY-PASTE FIX
    ## Why Agently Daily News Collector?

Unlike simple web scrapers or traditional news aggregators, this project is a full-fledged **LLM agent application**. It leverages the Agently framework to orchestrate a sophisticated, multi-step workflow that not only collects but also intelligently processes, summarizes, and assembles news briefings. It serves as a practical showcase for building complex, autonomous AI agents for information gathering and report generation.

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 AgentEra/Agently-Daily-News-Collector
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
NewsAPI.org
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. NewsAPI.org · recommended 1×
  2. huggingface/transformers · recommended 1×
  3. psf/requests · recommended 1×
  4. crummy/BeautifulSoup4 · recommended 1×
  5. codelucas/newspaper3k · recommended 1×
  • CATEGORY QUERY
    How to build an automated system for daily news collection and summarization using AI?
    you: not recommended
    AI recommended (in order):
    1. NewsAPI.org
    2. Hugging Face Transformers (huggingface/transformers)
    3. requests (psf/requests)
    4. BeautifulSoup (crummy/BeautifulSoup4)
    5. newspaper3k (codelucas/newspaper3k)
    6. Google Cloud Natural Language API
    7. feedparser (kurtmckee/feedparser)
    8. AWS Comprehend
    9. AWS Lambda
    10. EventBridge
    11. OpenAI API
    12. spaCy (explosion/spaCy)
    13. Scrapy (scrapy/scrapy)
    14. Gensim (piskvorky/gensim)

    AI recommended 14 alternatives but never named AgentEra/Agently-Daily-News-Collector. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for an LLM agent framework to automate information gathering and report generation.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. AutoGPT
    4. CrewAI
    5. Haystack
    6. Microsoft Semantic Kernel

    AI recommended 6 alternatives but never named AgentEra/Agently-Daily-News-Collector. 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 AgentEra/Agently-Daily-News-Collector?
    pass
    AI did not name AgentEra/Agently-Daily-News-Collector — 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 AgentEra/Agently-Daily-News-Collector in production, what risks or prerequisites should they evaluate first?
    pass
    AI named AgentEra/Agently-Daily-News-Collector 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 AgentEra/Agently-Daily-News-Collector solve, and who is the primary audience?
    pass
    AI did not name AgentEra/Agently-Daily-News-Collector — 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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AgentEra/Agently-Daily-News-Collector — 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