AI Slop Code Risk Monitor

perixtar/Tech-OA-Interview-Questions

SlopCodeMonitor badge for perixtar/Tech-OA-Interview-Questions Adjusted legacy signal; badge bands: 25 / 50 / 75 (different from dashboard bands).

Daily updated list of Tech Company OAs and Interview Problems. Save your time from finding them all over the internet.

3.7 Low pattern signal View on GitHub

Open-Source Code Quality, Security and Technical Debt Review

This report summarizes scanner evidence for perixtar/Tech-OA-Interview-Questions, a Python project with 5,897 GitHub stars. SynthScan examined 12,735 lines of code across 20 source files, recording 37 pattern matches distributed across 5 syntactic categories. The legacy adjusted pattern signal is 3.7 (Low 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.

3.7
Adjusted Signal
3.7
Raw Pattern Score
100%
Time Factor
2026-11-01
Last Push
5.9K
Stars
Python
Language
12.7K
Lines of Code
20
Files
37
Pattern Hits
2026-10-31
Scan Date
0.00
HC Hit Rate

Risk Review · Payload v1

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

Payload schema: 1.0.0 · Engine: 2.0.0 · Scoring: heuristic-density-v1 · Scan date: 2026-10-31.

Cognitive Ownership Risk 15.5/100 · LOW

Can maintainers explain intent, assumptions, and trade-offs? 33 finding(s).

Hallucinated Dependency & Supply Chain Risk 1.6/100 · LOW

Are imports declared and package/API names verified? 4 finding(s).

Agent Over-Engineering Ratio 9.7/100 · LOW

Are wrappers, guards, and repeated structures necessary? 24 finding(s).

PR Review Velocity Impact 18.8/100 · LOW

Which changes need focused human review? 37 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 0MEDIUM 8LOW 29

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 37 distinct pattern matches across 5 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.

Hyper-Verbose Identifiers24 hits · 26 pts
SeverityFileLineSnippetContext
LOWscripts/question_bank_pages.py66def strip_generated_navigation(prefix: str) -> str:CODE
LOWscripts/question_bank_pages.py273def assert_route_conservation(CODE
LOWscripts/question_bank_pages.py296def render_question_bank_pages(CODE
LOWscripts/test_question_bank_pages.py32 def test_render_and_reload_preserve_global_route_order(self) -> None:CODE
LOWscripts/test_question_bank_pages.py69 def test_duplicate_route_across_pages_fails_closed(self) -> None:CODE
LOWscripts/test_question_bank_pages.py91 def test_unmanaged_or_noncontiguous_continuation_pages_fail_closed(self) -> None:CODE
LOWscripts/test_question_bank_pages.py114 def test_single_row_over_hard_limit_fails_closed(self) -> None:CODE
LOWscripts/test_sync_practice_formats.py84 def test_missing_catalog_entry_uses_coding_route_fallback(self) -> None:CODE
LOW⚡scripts/test_sync_practice_formats.py104 def test_catalog_format_overrides_coding_route_fallback(self) -> None:CODE
LOW⚡scripts/test_sync_practice_formats.py113 def test_legacy_practice_format_header_is_renamed(self) -> None:CODE
LOW⚡scripts/test_sync_practice_formats.py123 def test_format_links_include_only_formats_in_the_table(self) -> None:CODE
LOW⚡scripts/test_sync_practice_formats.py132 def test_format_pages_contain_only_matching_rows(self) -> None:CODE
LOWscripts/test_sync_practice_formats.py148 def test_format_pages_use_the_same_byte_bounded_pagination(self) -> None:CODE
LOWscripts/test_sync_practice_formats.py189 def test_managed_catalogs_add_design_and_ai_coding_rows(self) -> None:CODE
LOWscripts/test_sync_practice_formats.py237 def test_missing_public_attribution_uses_factual_fallbacks(self) -> None:CODE
LOWscripts/test_sync_practice_formats.py262 def test_missing_sighting_date_preserves_the_first_sync_date(self) -> None:CODE
LOWscripts/test_sync_practice_formats.py291 def test_sync_compacts_favicons_to_keep_the_readme_renderable(self) -> None:CODE
LOWscripts/test_sync_practice_formats.py305 def test_sync_omits_protected_numeric_alias_rows(self) -> None:CODE
LOWscripts/test_sync_practice_formats.py339 def test_managed_rows_use_compact_rendering(self) -> None:CODE
LOWscripts/test_sync_practice_formats.py367 def test_managed_catalog_companies_are_added_to_company_list(self) -> None:CODE
LOWscripts/test_sync_practice_formats.py399 def test_company_list_is_case_insensitive_comma_safe_and_idempotent(self) -> None:CODE
LOWscripts/test_sync_practice_formats.py432 def test_refresh_freshness_accepts_spaced_and_compact_date_cells(self) -> None:CODE
LOWscripts/sync-practice-formats.py455def format_labels_in_display_order(counts: Counter) -> list[str]:CODE
LOWscripts/sync-practice-formats.py650def existing_format_page_paths() -> list[Path]:CODE
Modern AI Meta-Vocabulary8 hits · 16 pts
SeverityFileLineSnippetContext
MEDIUMREADME.md183|**Amazon**|[Design an Agentic Chatbot Domain](https://www.fastprep.io/low-level-design/agentic-chatbot-domain)|Low-leveCODE
MEDIUMREADME.md411|**Perplexity AI**|[Design Durable Long-Running Agentic Query Execution](https://www.fastprep.io/system-design/long-runnCODE
MEDIUMREADME.md537|**Amazon**|[Design Agentic Security Stream Detection](https://www.fastprep.io/system-design/agentic-security-stream-detCODE
MEDIUMREADME.md751|**Walmart**|[Design an Agent-Assisted Search Experience](https://www.fastprep.io/system-design/agentic-search-experiencCODE
MEDIUMformats/system-design.md103|**Perplexity AI**|[Design Durable Long-Running Agentic Query Execution](https://www.fastprep.io/system-design/long-runnCODE
MEDIUMformats/system-design.md116|**Amazon**|[Design Agentic Security Stream Detection](https://www.fastprep.io/system-design/agentic-security-stream-detCODE
MEDIUMformats/system-design.md139|**Walmart**|[Design an Agent-Assisted Search Experience](https://www.fastprep.io/system-design/agentic-search-experiencCODE
MEDIUMformats/low-level-design.md23|**Amazon**|[Design an Agentic Chatbot Domain](https://www.fastprep.io/low-level-design/agentic-chatbot-domain)|[![PractCODE
Fake / Example Data2 hits · 2 pts
SeverityFileLineSnippetContext
LOWREADME.md109|**Mercor**|[Expected Fake-Name Collisions](https://www.fastprep.io/problems/mercor-fake-name-expected-collisions)|CodinCODE
LOWformats/coding.md52|**Mercor**|[Expected Fake-Name Collisions](https://www.fastprep.io/problems/mercor-fake-name-expected-collisions)|[![PrCODE
Unused Imports2 hits · 2 pts
SeverityFileLineSnippetContext
LOWscripts/question_bank_pages.py4CODE
LOWscripts/sync-practice-formats.py27CODE
Deep Nesting1 hit · 1 pts
SeverityFileLineSnippetContext
LOWscripts/sync-practice-formats.py160CODE