REPOGEO REPORT · LITE

qualifire-dev/rogue

Default branch main · commit e1c5b563 · scanned 5/25/2026, 1:41:24 PM

GitHub: 1,024 stars · 161 forks

AI VISIBILITY SCORE

40 /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

3 / 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 qualifire-dev/rogue, 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

Add explicit positioning and counter false claims in README

Why:

CURRENT

# Rogue — AI Agent Evaluator & Red Team Platform

<div align="center">

<a href="https://trendshift.io/repositories/15191" target="_blank"></a>

**Stress-test your AI agents before attackers do.**

COPY-PASTE FIX

# Rogue — AI Agent Evaluator & Red Team Platform

<div align="center">

<a href="https://trendshift.io/repositories/15191" target="_blank"></a>

**Stress-test your AI agents before attackers do.**

**Rogue is a dedicated platform for evaluating and red teaming AI agents, not a general-purpose Go web framework.** It provides robust tools for ensuring your AI agents are secure, compliant, and performant in production environments.

mediumreadme#2

Add a 'Why Rogue?' or 'Comparison' section to the README

Why:

COPY-PASTE FIX

## Why Rogue?
Unlike general-purpose LLM frameworks or basic evaluation scripts, Rogue is purpose-built for comprehensive AI agent security and compliance. It offers integrated red teaming with 75+ vulnerabilities and 8 compliance frameworks, alongside automatic policy-based evaluation, providing a holistic platform for hardening your agents against both business risks and adversarial attacks.

lowreadme#3

Clarify the project's license in the README

Why:

COPY-PASTE FIX

## License
This project is licensed under [insert specific license name(s) here, e.g., 'a custom license combining Apache 2.0 and MIT terms']. See the [LICENSE file](./LICENSE) for full details.

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 qualifire-dev/rogue

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

langchain-ai/langchain

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

langchain-ai/langchain · recommended 1×
LangSmith · recommended 1×
openai/evals · recommended 1×
Scale AI · recommended 1×
Appen · recommended 1×

CATEGORY QUERY
How to evaluate AI agent behavior and ensure compliance with predefined business policies?
you: not recommended
AI recommended (in order):
1. LangChain (langchain-ai/langchain)
2. LangSmith
3. OpenAI Evals (openai/evals)
4. Scale AI
5. Appen
6. W&B Prompts (wandb/wandb)
7. Elasticsearch (elastic/elasticsearch)
8. Logstash (elastic/logstash)
9. Kibana (elastic/kibana)
10. Splunk
11. Guardrails AI (guardrails-ai/guardrails)
12. Ragas (explodinggradients/ragas)
AI recommended 12 alternatives but never named qualifire-dev/rogue. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are the best tools for red teaming LLM agents to uncover adversarial security vulnerabilities?
you: not recommended
AI recommended (in order):
1. Garak
2. LLM-Defender
3. Adversarial GLUE
4. PromptInject
5. OWASP Top 10 for LLM Applications
6. Red Teaming Toolkit for LLMs
7. LangChain
8. LlamaIndex
AI recommended 8 alternatives but never named qualifire-dev/rogue. 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 qualifire-dev/rogue?
pass
AI named qualifire-dev/rogue explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts qualifire-dev/rogue in production, what risks or prerequisites should they evaluate first?
pass
AI named qualifire-dev/rogue 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 qualifire-dev/rogue solve, and who is the primary audience?
pass
AI named qualifire-dev/rogue explicitly
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 qualifire-dev/rogue. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

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HTML

<a href="https://repogeo.com/en/r/qualifire-dev/rogue"><img src="https://repogeo.com/badge/qualifire-dev/rogue.svg" alt="RepoGEO" /></a>

Pro

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qualifire-dev/rogue — 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