AI Slop Code RIsk Monitor

steven2358/awesome-generative-ai

A curated list of modern Generative Artificial Intelligence projects and services

60.4 High pattern signal View on GitHub

Maintenance and Governance Review

This report summarizes scanner evidence for steven2358/awesome-generative-ai with 12,723 GitHub stars. SynthScan examined 936 lines of code across 6 source files, recording 17 pattern matches distributed across 2 syntactic categories. The legacy adjusted pattern signal is 60.4 (High pattern signal); it is not an authorship estimate.

Use the findings to ask whether maintainers can explain intent, verify dependencies, simplify unnecessary scaffolding, and focus review effort. Risk Payload v1 adds ownership, supply-chain, over-engineering, and review-effort vectors when available. These are prompts for human verification, not probabilities, security findings, or measured maintenance costs.

60.4
Adjusted Signal
60.4
Raw Pattern Score
100%
Time Factor
2026-10-03
Last Push
12.7K
Stars
—
Language
936
Lines of Code
6
Files
17
Pattern Hits
2026-10-12
Scan Date
1.00
HC Hit Rate

Risk Review · v3

Use each vector to guide manual verification of the underlying findings.

Cognitive Ownership Risk 95.1/100 · CRITICAL

Can maintainers explain intent, assumptions, and trade-offs? 17 finding(s).

Hallucinated Dependency & Supply Chain Risk 0.0/100 · LOW

Are imports declared and package/API names verified? 0 finding(s).

Agent Over-Engineering Ratio 0.0/100 · LOW

Are wrappers, guards, and repeated structures necessary? 0 finding(s).

PR Review Velocity Impact 97.5/100 · CRITICAL

Which changes need focused human review? 17 finding(s).

What These Metrics Mean

Adjusted Signal
Legacy pattern score normalized per 1,000 scanned lines and multiplied by the repository-level time factor. It is not an estimate of AI authorship.
Raw Pattern Score
Sum of severity- and context-weighted pattern findings before applying the time factor.
Time Factor
A coarse multiplier based on repository last-push metadata. It does not identify when individual code was written.
Pattern Hits
Count of configured pattern findings. Review each location and surrounding code before acting.
HC Hit Rate
High- and critical-severity findings per scanned file. Severity is a configured detector weight, not proof of a vulnerability or authorship.
Lines / Files
Scan coverage denominators used by the legacy normalized score.

Pattern-Signal History

This chart tracks the legacy adjusted pattern score across scan runs. Changes can reflect source changes, scan coverage, or detector/scoring versions; they do not measure AI adoption or prove that a team refactored code. Compare runs only when their scoring versions are compatible. The dashed line tracks the raw pattern-hit count.

Severity Breakdown

Groups findings by configured severity weight. Severity is not a confidence estimate, security rating, or proof that a package is missing. Verify imports against the project's manifests and inspect each finding in its local design context.

CRITICAL 0HIGH 6MEDIUM 11LOW 0

Directory Score Breakdown

This horizontal bar chart shows where configured pattern scores accumulate across directories. Treat the bars as locations to inspect, not as evidence of authorship or code quality. Use the file-level findings to decide whether a directory needs a focused ownership, dependency, complexity, or review check.

Pattern Findings

The scanner identified 17 distinct pattern matches across 2 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a detector match to inspect in context. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.

Reading the findings table: The Severity column indicates the configured finding weight (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — legacy comment-context matches receive a ×1.5 score weight. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier under the legacy scoring model.

Synthetic Comment Markers6 hits · 32 pts
SeverityFileLineSnippetContext
HIGHDISCOVERIES.md204- [PlantPhotoAI](https://www.plantphotoai.com/) - Free AI-generated plant photos with botanical accuracy.CODE
HIGH⚡README.md67- [Meta AI](https://www.meta.ai/) - Meta AI assistant to get things done, create AI-generated images, get answers. BuiltCODE
HIGHREADME.md330- [Photo AI](https://photoai.com/ai-avatars) - Create your own AI-generated avatars.CODE
HIGHREADME.md333- [RunDiffusion](https://rundiffusion.com/) - Cloud-based workspace for creating AI-generated art.CODE
HIGHREADME.md392- [Affogato](https://affogato.ai/) - Create AI-generated product video ads for TikTok, Reels, and Shorts.CODE
HIGHREADME.md438- [Scenario](https://www.scenario.com/) - AI-generated gaming assets.CODE
Modern AI Meta-Vocabulary11 hits · 24 pts
SeverityFileLineSnippetContext
MEDIUMDISCOVERIES.md47- [Atlas UI 3](https://github.com/sandialabs/atlas-ui-3) - Full-stack LLM chat interface with MCP tool integration, multCODE
MEDIUMDISCOVERIES.md137- [Pixee](https://www.pixee.ai/) - An agentic application security platform for triaging and fixing vulnerabilities in cCODE
MEDIUMDISCOVERIES.md147- [Agentic Radar](https://github.com/splx-ai/agentic-radar) - Open-source CLI for analyzing agentic workflows and surfacCODE
MEDIUMDISCOVERIES.md182- [Network-AI](https://github.com/Jovancoding/Network-AI) - A TypeScript/Node.js multi-agent orchestrator with shared stCODE
MEDIUM⚡README.md59- [Kimi K2](https://github.com/moonshotai/Kimi-K2) - A series of open-source MoE language models by Moonshot AI for agenCODE
MEDIUM⚡README.md60- [GLM](https://github.com/zai-org/GLM-5) - A series of open-source MoE language models by Z.ai for agentic tasks. #openCODE
MEDIUMREADME.md192- [Qodo](https://www.qodo.ai/) - AI code review tool with agentic workflows for IDEs, pull requests, and security.CODE
MEDIUMREADME.md239- [Agentset](https://agentset.ai/) - An open-source platform for building and evaluating RAG and agentic applications. [CODE
MEDIUMREADME.md245- [Bifrost](https://github.com/maximhq/bifrost) - An open-source LLM gateway with routing, load balancing, guardrails, aCODE
MEDIUMREADME.md282- [Davika](https://github.com/stitionai/devika) - An agentic AI software engineer. #opensourceCODE
MEDIUMREADME.md285- [Claude Code](https://code.claude.com) - Anthropic's agentic coding tool that lives in your terminal and helps you turCODE