AI Slop Code RIsk Monitor

shuaibiyy/awesome-tf

Curated list of resources on HashiCorp's Terraform and OpenTofu

18.1 Elevated pattern signal View on GitHub

Maintenance and Governance Review

This report summarizes scanner evidence for shuaibiyy/awesome-tf with 6,612 GitHub stars. SynthScan examined 1,093 lines of code across 10 source files, recording 14 pattern matches distributed across 3 syntactic categories. The legacy adjusted pattern signal is 18.1 (Elevated 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.

18.1
Adjusted Signal
18.1
Raw Pattern Score
100%
Time Factor
2026-10-06
Last Push
6.6K
Stars
—
Language
1.1K
Lines of Code
10
Files
14
Pattern Hits
2026-10-12
Scan Date
0.00
HC Hit Rate

Risk Review · v3

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

Cognitive Ownership Risk 59.5/100 · HIGH

Can maintainers explain intent, assumptions, and trade-offs? 14 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 23.1/100 · LOW

Are wrappers, guards, and repeated structures necessary? 8 finding(s).

PR Review Velocity Impact 63.5/100 · HIGH

Which changes need focused human review? 14 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

Run additional scans to build a history of the legacy pattern signal. Score changes are not a measure of AI adoption or code quality.

No multi-scan history yet — run the scanner again to build trend data.

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 0MEDIUM 4LOW 10

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 14 distinct pattern matches across 3 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.

Modern AI Meta-Vocabulary4 hits · 12 pts
SeverityFileLineSnippetContext
MEDIUM⚡README.md341- [terraform-provider-openrouter](https://github.com/cloudopsworks/terraform-provider-openrouter) - Manage OpenRouter asCODE
MEDIUM⚡README.md342- [terraform-provider-plancost](https://github.com/plancost/terraform-provider-plancost) - Terraform provider for Azure CODE
MEDIUM⚡README.md349- [terraform-provider-openrouter](https://github.com/cloudopsworks/terraform-provider-openrouter) - Manage OpenRouter asCODE
MEDIUM⚡README.md350- [terraform-provider-plancost](https://github.com/plancost/terraform-provider-plancost) - Terraform provider for Azure CODE
Hyper-Verbose Identifiers8 hits · 6 pts
SeverityFileLineSnippetContext
LOW.github/scripts/test_check_new_links.py13 def test_markdown_forms_and_unchanged_broken_link(self):CODE
LOW.github/scripts/test_check_new_links.py52 def test_description_only_does_not_check_existing_broken_url(self):STRING
LOW.github/scripts/test_check_new_links.py55 def test_new_http_url_is_rejected(self):STRING
LOW⚡.github/scripts/test_check_new_links.py66 def test_reachable_and_redirect_destination(self):STRING
LOW⚡.github/scripts/test_check_new_links.py71 def test_hard_network_failures(self):STRING
LOW⚡.github/scripts/test_check_new_links.py80 def test_bot_responses_and_exclusions_need_review(self):STRING
LOW⚡.github/scripts/test_check_new_links.py88 def test_incomplete_report_and_execution_failure(self):STRING
LOW⚡.github/scripts/test_check_new_links.py95 def test_real_requests_redirects_and_review_responses(self):STRING
Deep Nesting2 hits · 2 pts
SeverityFileLineSnippetContext
LOW.github/scripts/check_new_links.py27CODE
LOW.github/scripts/check_new_links.py67CODE