Repository Analysis

phuryn/pm-skills

PM Skills Marketplace: 100+ agentic skills, commands, and plugins — from discovery to strategy, execution, launch, and growth.

34.3 Strong AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of phuryn/pm-skills with 23,667 GitHub stars. SynthScan v2.0 examined 13,136 lines of code across 139 source files, recording 249 pattern matches distributed across 8 syntactic categories. The overall adjusted score of 34.3 places this repository in the Strong AI signal band.

The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).

34.3
Adjusted Score
34.3
Raw Score
100%
Time Factor
2026-07-03
Last Push
23.7K
Stars
Language
13.1K
Lines of Code
139
Files
249
Pattern Hits
2026-07-14
Scan Date
0.00
HC Hit Rate

What These Metrics Mean

Adjusted Score
Primary synthetic code indicator. Raw score normalised per 1,000 lines of code and multiplied by the temporal discount factor. This is the definitive comparative metric — use it to rank repositories by AI authorship density.
Raw Score
The unmodified sum of all severity-weighted, context-multiplied pattern match scores before temporal discounting. Reflects the absolute signal strength independent of when the repository was last active.
Time Factor
The temporal discount multiplier (0–100%) applied to the raw score. Repositories last updated before ChatGPT's launch (Nov 2022) receive a 5% factor. Full signal is only assigned to repositories active in the post-adoption era (Jan 2024+).
Pattern Hits
Total count of individual pattern matches across all files and categories. A high hit count with a low score may indicate a very large codebase with isolated AI snippets; a low count with a high score indicates dense, concentrated AI signatures.
HC Hit Rate
High+Critical pattern hits per file, averaged across the repository. This orthogonal signal catches repositories where a few files are densely packed with high-severity AI tells — a strong indicator even when the normalised score appears moderate due to codebase size.
Lines of Code / Files
Total lines and files analysed. The scanner examines 94 file extensions. These denominators are used to normalise the score, enabling fair comparison between repositories of vastly different sizes.

Score History

This chart maps the temporal evolution of the adjusted synthetic code score across successive scan runs. An upward trajectory indicates ongoing incorporation of AI-generated code or expanding LLM-assisted scaffolding; a stable or declining trajectory may reflect active human refactoring, code removal, or the adoption of stricter authorship policies. The dashed secondary line (right axis) independently tracks total raw pattern hit count, which can diverge from the normalised score when codebase size changes significantly between scans.

Severity Breakdown

Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.

CRITICAL 0HIGH 0MEDIUM 7LOW 242

Directory Score Breakdown

This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.

Pattern Findings

The scanner identified 249 distinct pattern matches across 8 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. 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 diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.

Structural Annotation Overuse224 hits · 410 pts
SeverityFileLineSnippetContext
LOWREADME.md67# Step 1: Add the marketplaceCOMMENT
LOWREADME.md70# Step 2: Install individual pluginsCOMMENT
LOWREADME.md87# Step 1: Add the marketplaceCOMMENT
LOWREADME.md90# Step 2: Install the plugins you wantCOMMENT
LOWpm-product-strategy/commands/pricing.md20### Step 1: Understand the Pricing ContextCOMMENT
LOWpm-product-strategy/commands/pricing.md29### Step 2: Analyze Pricing ModelsCOMMENT
LOWpm-product-strategy/commands/pricing.md43### Step 3: Competitive Pricing AnalysisCOMMENT
LOWpm-product-strategy/commands/pricing.md51### Step 4: Willingness to Pay EstimationCOMMENT
LOWpm-product-strategy/commands/pricing.md61### Step 5: Generate Pricing RecommendationCOMMENT
LOWpm-product-strategy/commands/pricing.md115### Step 6: Offer Next StepsCOMMENT
LOWpm-product-strategy/commands/market-scan.md20### Step 1: Understand the ContextCOMMENT
LOWpm-product-strategy/commands/market-scan.md28### Step 2: Run the AnalysisCOMMENT
LOWpm-product-strategy/commands/market-scan.md49### Step 3: SynthesizeCOMMENT
LOWpm-product-strategy/commands/market-scan.md57### Step 4: Generate ReportCOMMENT
LOWpm-product-strategy/commands/market-scan.md115### Step 5: Offer Next StepsCOMMENT
LOWpm-product-strategy/commands/business-model.md157### Step 1: Gather ContextCOMMENT
LOWpm-product-strategy/commands/business-model.md165### Step 2: Generate the Selected Framework(s)COMMENT
LOWpm-product-strategy/commands/business-model.md169### Step 3: Save and IterateCOMMENT
LOWpm-product-strategy/commands/strategy.md20### Step 1: Understand the ProductCOMMENT
LOWpm-product-strategy/commands/strategy.md33### Step 2: Build the Strategy CanvasCOMMENT
LOWpm-product-strategy/commands/strategy.md51### Step 3: Generate Strategy DocumentCOMMENT
LOWpm-product-strategy/commands/strategy.md105### Step 4: Offer Next StepsCOMMENT
LOWpm-product-strategy/commands/value-proposition.md20### Step 1: Understand the Product and MarketCOMMENT
LOWpm-product-strategy/commands/value-proposition.md32### Step 2: Build the Value PropositionCOMMENT
LOWpm-product-strategy/commands/value-proposition.md59### Step 3: Save and Offer Next StepsCOMMENT
LOWpm-market-research/commands/research-users.md20### Step 1: Accept Research InputsCOMMENT
LOWpm-market-research/commands/research-users.md35### Step 2: Build PersonasCOMMENT
LOWpm-market-research/commands/research-users.md44### Step 3: Segment UsersCOMMENT
LOWpm-market-research/commands/research-users.md53### Step 4: Map the Customer JourneyCOMMENT
LOWpm-market-research/commands/research-users.md62### Step 5: Generate Research ReportCOMMENT
LOWpm-market-research/commands/research-users.md108### Step 6: Offer Next StepsCOMMENT
LOWpm-market-research/commands/analyze-feedback.md20### Step 1: Accept Feedback DataCOMMENT
LOWpm-market-research/commands/analyze-feedback.md32### Step 2: AnalyzeCOMMENT
LOWpm-market-research/commands/analyze-feedback.md42### Step 3: Generate Analysis ReportCOMMENT
LOWpm-market-research/commands/analyze-feedback.md91### Step 4: Offer Next StepsCOMMENT
LOWpm-market-research/commands/competitive-analysis.md20### Step 1: Understand the Competitive ContextCOMMENT
LOWpm-market-research/commands/competitive-analysis.md28### Step 2: Identify CompetitorsCOMMENT
LOWpm-market-research/commands/competitive-analysis.md37### Step 3: Analyze Each CompetitorCOMMENT
LOWpm-market-research/commands/competitive-analysis.md47### Step 4: Generate Competitive AnalysisCOMMENT
LOWpm-market-research/commands/competitive-analysis.md85### Step 5: Offer Next StepsCOMMENT
LOWpm-data-analytics/commands/analyze-cohorts.md20### Step 1: Accept Data or Define AnalysisCOMMENT
LOWpm-data-analytics/commands/analyze-cohorts.md26### Step 2: Define CohortsCOMMENT
LOWpm-data-analytics/commands/analyze-cohorts.md34### Step 3: AnalyzeCOMMENT
LOWpm-data-analytics/commands/analyze-cohorts.md51### Step 4: Generate ReportCOMMENT
LOWpm-data-analytics/commands/analyze-cohorts.md88### Step 5: Offer Next StepsCOMMENT
LOWpm-data-analytics/commands/write-query.md20### Step 1: Understand the QuestionCOMMENT
LOWpm-data-analytics/commands/write-query.md28### Step 2: Determine SchemaCOMMENT
LOWpm-data-analytics/commands/write-query.md39### Step 3: Generate QueryCOMMENT
LOWpm-data-analytics/commands/write-query.md49### Step 4: Present and IterateCOMMENT
LOWpm-data-analytics/commands/analyze-test.md20### Step 1: Accept Test DataCOMMENT
LOWpm-data-analytics/commands/analyze-test.md28### Step 2: Validate Test DesignCOMMENT
LOWpm-data-analytics/commands/analyze-test.md38### Step 3: Analyze ResultsCOMMENT
LOWpm-data-analytics/commands/analyze-test.md48### Step 4: Generate AnalysisCOMMENT
LOWpm-data-analytics/commands/analyze-test.md96### Step 5: Offer Next StepsCOMMENT
LOWpm-data-analytics/skills/sql-queries/SKILL.md13### Step 1: Understand Your Database SchemaCOMMENT
LOWpm-data-analytics/skills/sql-queries/SKILL.md18### Step 2: Process Your RequestCOMMENT
LOWpm-data-analytics/skills/sql-queries/SKILL.md23### Step 3: Generate Optimized QueryCOMMENT
LOWpm-data-analytics/skills/sql-queries/SKILL.md29### Step 4: Explain and TestCOMMENT
LOWpm-data-analytics/skills/cohort-analysis/SKILL.md13### Step 1: Read and Validate Your DataCOMMENT
LOWpm-data-analytics/skills/cohort-analysis/SKILL.md19### Step 2: Generate Quantitative AnalysisCOMMENT
164 more matches not shown…
Decorative Section Separators6 hits · 18 pts
SeverityFileLineSnippetContext
MEDIUMvalidate_plugins.py28# ─── Configuration ───────────────────────────────────────────────────────────COMMENT
MEDIUMvalidate_plugins.py47# ─── ANSI Colors ─────────────────────────────────────────────────────────────COMMENT
MEDIUMvalidate_plugins.py60# ─── Helpers ─────────────────────────────────────────────────────────────────COMMENT
MEDIUMvalidate_plugins.py94# ─── Validators ──────────────────────────────────────────────────────────────COMMENT
MEDIUMvalidate_plugins.py313# ─── Main Validator ──────────────────────────────────────────────────────────COMMENT
MEDIUM.github/workflows/tag-on-merge.yml101 # ── Release gates ────────────────────────────────────────────────────COMMENT
Hyper-Verbose Identifiers13 hits · 14 pts
SeverityFileLineSnippetContext
LOWvalidate_plugins.py289def validate_cross_references(plugin_dir: str, skill_names: list[str]) -> ValidationResult:CODE
LOWtests/test_consistency.py59 def test_marketplace_lists_exactly_the_plugins_on_disk(self):CODE
LOWtests/test_consistency.py69 def test_sources_point_at_matching_directories(self):CODE
LOWtests/test_consistency.py81 def test_all_versions_identical_and_match_changelog(self):CODE
LOWtests/test_consistency.py100 def test_headings_well_formed_dated_unique_descending(self):CODE
LOWtests/test_consistency.py135 def test_root_readme_headline_counts(self):CODE
LOWtests/test_consistency.py148 def test_marketplace_description_counts(self):CODE
LOWtests/test_consistency.py164 def test_root_readme_per_plugin_counts(self):CODE
LOWtests/test_consistency.py184 def test_plugin_readme_section_counts(self):CODE
LOWtests/test_consistency.py209 def test_plugin_readme_command_refs_exist(self):CODE
LOWtests/test_validator.py21 def test_none_without_frontmatter(self):CODE
LOWtests/test_validator.py24 def test_none_when_unterminated(self):CODE
LOWtests/test_validator.py33 def test_excludes_frontmatter(self):CODE
Excessive Try-Catch Wrapping1 hit · 2 pts
SeverityFileLineSnippetContext
MEDIUMvalidate_plugins.py478 print(f"Error: {base_path} is not a directory")CODE
Deep Nesting2 hits · 2 pts
SeverityFileLineSnippetContext
LOWvalidate_plugins.py370CODE
LOWtests/test_validator.py40CODE
Redundant / Tautological Comments1 hit · 2 pts
SeverityFileLineSnippetContext
LOWvalidate_plugins.py260 # Check if command references skills (informational)COMMENT
Unused Imports1 hit · 1 pts
SeverityFileLineSnippetContext
LOWvalidate_plugins.py24CODE
Over-Commented Block1 hit · 1 pts
SeverityFileLineSnippetContext
LOW.github/workflows/tag-on-merge.yml1name: Tag and release from CHANGELOGCOMMENT