RRepoGEO

REPOGEO REPORT · LITE

usewhale/DeepSeek-Code-Whale

Default branch main · commit 9ff4e6bb · scanned 6/17/2026, 2:41:27 AM

GitHub: 654 stars · 43 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 usewhale/DeepSeek-Code-Whale, 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 the README's opening to emphasize core differentiators

    Why:

    CURRENT
    <b>Whale — AI coding agent for DeepSeek, in any environment.</b><br>Long context, tools, and programmable workflows —<br>start in the terminal, scale to desktop and beyond.
    COPY-PASTE FIX
    <b>Whale — the blazingly fast, terminal-first AI coding agent for DeepSeek.</b><br>Achieve ~98% prompt cache hit rates, 1M context, MCP tools, and dynamic workflows, starting in your terminal and scaling anywhere.
  • mediumtopics#2
    Expand topics to include more specific keywords

    Why:

    CURRENT
    coding-agent, deepseek, deepseek-agent, deepseek-cli, deepseek-coding-agent, go, llm, mcp, skills, terminal
    COPY-PASTE FIX
    coding-agent, deepseek, deepseek-agent, deepseek-cli, deepseek-coding-agent, go, llm, mcp, skills, terminal, cli, productivity, developer-tools, ai-assistant, code-generation, prompt-caching, long-context
  • mediumreadme#3
    Add a 'Why Whale?' or 'Key Differentiators' section to the README

    Why:

    COPY-PASTE FIX
    Add a new section to the README, perhaps after 'Quick Start', titled 'Why Whale?' or 'Key Differentiators'. This section should explicitly list and elaborate on: 1. DeepSeek-Native: Optimized specifically for DeepSeek models. 2. Terminal-First & Blazingly Fast: Designed for speed and efficiency in the CLI. 3. High Cache Hit Rate: ~98% prompt cache hit for rapid iteration. 4. Long Context & MCP Tools: Handles complex tasks with 1M context and powerful tools. 5. Programmable Workflows: Dynamic and customizable agent behavior.

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 usewhale/DeepSeek-Code-Whale
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Cursor
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Cursor · recommended 2×
  2. Continue · recommended 2×
  3. GPT-Engineer · recommended 2×
  4. aider · recommended 1×
  5. smol-developer · recommended 1×
  • CATEGORY QUERY
    What are the best terminal-based AI coding agents for fast, efficient development workflows?
    you: not recommended
    AI recommended (in order):
    1. Cursor
    2. Continue
    3. aider
    4. GPT-Engineer
    5. smol-developer
    6. OpenDevin

    AI recommended 6 alternatives but never named usewhale/DeepSeek-Code-Whale. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an AI coding agent specifically for DeepSeek models with extensive context and tool integration.
    you: not recommended
    AI recommended (in order):
    1. Cursor
    2. Continue
    3. Open Interpreter
    4. Aider
    5. GPT-Engineer

    AI recommended 5 alternatives but never named usewhale/DeepSeek-Code-Whale. 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 usewhale/DeepSeek-Code-Whale?
    pass
    AI did not name usewhale/DeepSeek-Code-Whale — 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 usewhale/DeepSeek-Code-Whale in production, what risks or prerequisites should they evaluate first?
    pass
    AI named usewhale/DeepSeek-Code-Whale 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 usewhale/DeepSeek-Code-Whale solve, and who is the primary audience?
    pass
    AI did not name usewhale/DeepSeek-Code-Whale — 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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usewhale/DeepSeek-Code-Whale — 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