A
licenseA
qualityB
maintenanceProvides local, deterministic scoring and detailed auditing of text for AI-writing patterns via two read-only tools, with no network calls or language models.
4
2
8 npm
2
MIT
signs-of-ai
by peopleworks
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TDQS
A4.4/5.0
Scored across 10 tools
Disambiguation4/5
Each tool targets a distinct analysis vector—stylometry, perplexity, hidden characters, citation consistency, exact copying, paraphrased copying, authorship baseline, and report generation—so most are easy to distinguish. The main ambiguity is between check_originality and check_paraphrase, and secondarily among analyze_ai_writing, measure_predictability, and write_report as related ways of assessing AI-like writing.
Naming Consistency5/5
All tool names follow a consistent imperative verb + object pattern in snake_case, such as search_catalog, check_citations, and write_report. The only minor deviation is compare_to_baseline with its preposition, but it still fits the overall pattern clearly.
Tool Count5/5
Ten tools cover a broad but coherent scope for an AI-writing analysis server: core analysis, predictability, authorship baseline, plagiarism and paraphrase checks, character inspection, citation validation, a reference catalog, and report generation. Each tool earns its place and none feel redundant.
Completeness5/5
The tool surface covers the full workflow of a document review for AI-writing signs: analyze stylistic signals, measure predictability, check for copying and paraphrasing, inspect hidden characters, validate citations, extract distinctive phrases for further checking, and produce a final report. Live web search and whole-internet plagiarism indexing are explicitly out of scope by design.
Maintenance
ActivityActive
ResponsivenessWithin a week