Repository Analysis

DietrichGebert/ponytail

Makes your AI agent think like the laziest senior dev in the room. The best code is the code you never wrote.

26.8 Moderate AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of DietrichGebert/ponytail, a JavaScript project with 82,779 GitHub stars. SynthScan v2.0 examined 12,063 lines of code across 137 source files, recording 133 pattern matches distributed across 12 syntactic categories. The overall adjusted score of 26.8 places this repository in the Moderate 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).

26.8
Adjusted Score
26.8
Raw Score
100%
Time Factor
2026-07-10
Last Push
82.8K
Stars
JavaScript
Language
12.1K
Lines of Code
137
Files
133
Pattern Hits
2026-07-14
Scan Date
0.25
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 34MEDIUM 29LOW 70

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 133 distinct pattern matches across 12 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.

Cross-Language Confusion (JS/TS)22 hits · 110 pts
SeverityFileLineSnippetContext
HIGHtests/correctness.test.js32 'def validate_email(email):\n return True',CODE
HIGHtests/correctness.test.js83print(df['amount'].sum())`,CODE
HIGHtests/correctness.test.js118print(351)`,CODE
HIGHtests/correctness.test.js129print(351)`,CODE
HIGHtests/hermes-plugin.test.js80print(json.dumps({'skills': ctx.skills, 'hooks': ctx.hooks, 'commands': ctx.commands}, sort_keys=True))CODE
HIGHtests/hermes-plugin.test.js105print(json.dumps({'ctx': ctx}))CODE
HIGHtests/hermes-plugin.test.js136print(json.dumps({CODE
HIGHtests/hermes-plugin.test.js159print(json.dumps({'ctx': ctx}))CODE
HIGHtests/hermes-plugin.test.js186print(json.dumps({'message': message, 'context': injected['context']}))CODE
HIGHtests/hermes-plugin.test.js210print(json.dumps(result))CODE
HIGHtests/hermes-plugin.test.js226print(json.dumps(cases, sort_keys=True))CODE
HIGHbenchmarks/correctness.js104 print("FAIL: no validator function found")CODE
HIGHbenchmarks/correctness.js121 print("FAIL: " + "; ".join(failures))CODE
HIGHbenchmarks/correctness.js123print("PASS")CODE
HIGHbenchmarks/correctness.js213 print("PASS")CODE
HIGHbenchmarks/correctness.js216 print("FAIL: output was: " + repr(output[:200]))CODE
HIGHbenchmarks/correctness.test.js11const WRONG_EMAIL = '```python\ndef validate_email(e):\n return True # accepts everything\n```';CODE
HIGHbenchmarks/robustness-audit.js39 good: 'def is_prime(n):\n if n < 2: return False\n for i in range(2, int(n**0.5)+1):\n if n % i == 0: rCODE
HIGHbenchmarks/robustness-audit.js40 bad: 'def is_prime(n):\n for i in range(2, n):\n if n % i == 0: return False\n return True' },CODE
HIGHbenchmarks/robustness-audit.js111 good: 'def validate_credit_card(n):\n d=[int(c) for c in str(n) if c.isdigit()]\n if len(d)<13: return False\nCODE
HIGHbenchmarks/robustness-audit.js116 good: 'import ipaddress\ndef validate_ipv4(s):\n try:\n ipaddress.IPv4Address(s); return True\n except CODE
HIGHbenchmarks/robustness-audit.js147print('PASS')`;CODE
Cross-Language Confusion11 hits · 78 pts
SeverityFileLineSnippetContext
HIGHbenchmarks/agentic/tasks.py446# `null`: JSON.parse("null") returns null, which slips past a try/catch around parsing, thenCOMMENT
HIGHbenchmarks/agentic/tasks.py456# good: rejects a non-object body (incl. null) with 400 and stays up.COMMENT
HIGHbenchmarks/agentic/tasks.py453 "// Listen on process.env.PORT || 3000.\n"CODE
HIGHbenchmarks/agentic/tasks.py470 const id = m[1] ? Number(m[1]) : null;CODE
HIGHbenchmarks/agentic/tasks.py471 if (id === null) {CODE
HIGHbenchmarks/agentic/tasks.py476 if (body === null || typeof body !== 'object' || Array.isArray(body)) return send(res, 400, { error: 'body must beCODE
HIGHbenchmarks/agentic/tasks.py487server.listen(process.env.PORT || 3000);CODE
HIGHbenchmarks/agentic/tasks.py505 const id = m[1] ? Number(m[1]) : null;CODE
HIGHbenchmarks/agentic/tasks.py506 if (id === null) {CODE
HIGHbenchmarks/agentic/tasks.py520server.listen(process.env.PORT || 3000);CODE
HIGHbenchmarks/agentic/tasks.py806 "clients. Listen on process.env.PORT || 3000."),CODE
Decorative Section Separators22 hits · 60 pts
SeverityFileLineSnippetContext
MEDIUMbenchmarks/agentic/tasks.py67# ======================================================================================COMMENT
MEDIUMbenchmarks/agentic/tasks.py69# ======================================================================================COMMENT
MEDIUMbenchmarks/agentic/tasks.py311# ======================================================================================COMMENT
MEDIUMbenchmarks/agentic/tasks.py315# ======================================================================================COMMENT
MEDIUMbenchmarks/agentic/tasks.py361# ======================================================================================COMMENT
MEDIUMbenchmarks/agentic/tasks.py370# ======================================================================================COMMENT
MEDIUMbenchmarks/agentic/tasks.py444# ======================================================================================COMMENT
MEDIUMbenchmarks/agentic/tasks.py450# ======================================================================================COMMENT
MEDIUMbenchmarks/agentic/tasks.py576# ======================================================================================COMMENT
MEDIUMbenchmarks/agentic/tasks.py108# ======================================================================================COMMENT
MEDIUMbenchmarks/agentic/tasks.py110# ======================================================================================COMMENT
MEDIUMbenchmarks/agentic/tasks.py168# ======================================================================================COMMENT
MEDIUMbenchmarks/agentic/tasks.py170# ======================================================================================COMMENT
MEDIUMbenchmarks/agentic/tasks.py211# ======================================================================================COMMENT
MEDIUMbenchmarks/agentic/tasks.py214# ======================================================================================COMMENT
MEDIUMbenchmarks/agentic/tasks.py262# ======================================================================================COMMENT
MEDIUMbenchmarks/agentic/tasks.py264# ======================================================================================COMMENT
MEDIUMbenchmarks/agentic/tasks.py413# ======================================================================================COMMENT
MEDIUMbenchmarks/agentic/tasks.py591# ======================================================================================COMMENT
MEDIUMbenchmarks/agentic/tasks.py798# ======================================================================================COMMENT
MEDIUMbenchmarks/agentic/tasks.py939 # ==================================================================================COMMENT
MEDIUMbenchmarks/agentic/tasks.py943 # ==================================================================================COMMENT
Excessive Try-Catch Wrapping53 hits · 44 pts
SeverityFileLineSnippetContext
LOW__init__.py61 except Exception:CODE
LOW__init__.py149 except Exception:CODE
LOW__init__.py186 except Exception:CODE
MEDIUMexamples/csv-sum.md49 print("Error: sales.csv not found")CODE
MEDIUMexamples/csv-sum.md51 print("Error: 'amount' column not found")CODE
LOWbenchmarks/correctness.js201except Exception as e:CODE
LOWbenchmarks/robustness-audit.js145 except Exception as e: print('EXC', args, e); sys.exit(1)CODE
LOWbenchmarks/agentic/run.py83 except Exception: return 0CODE
LOWbenchmarks/agentic/run.py101 except Exception: return 0, 0, 0, 0CODE
LOWbenchmarks/agentic/run.py130 except Exception: passCODE
LOWbenchmarks/agentic/run.py269 except Exception: passCODE
LOWbenchmarks/agentic/run.py335 except Exception: passCODE
LOWbenchmarks/agentic/run.py337 except Exception as e:CODE
LOWbenchmarks/agentic/run.py400 except Exception: return "unknown"CODE
LOWbenchmarks/agentic/run.py452 except Exception as e:CODE
LOWbenchmarks/agentic/tasks.py79 except Exception as e:CODE
LOWbenchmarks/agentic/tasks.py84 except Exception:CODE
LOWbenchmarks/agentic/tasks.py323 except Exception as e:CODE
LOWbenchmarks/agentic/tasks.py331 except Exception:CODE
LOWbenchmarks/agentic/tasks.py381 except Exception as e:CODE
LOWbenchmarks/agentic/tasks.py385 except Exception:CODE
LOWbenchmarks/agentic/tasks.py436 except Exception: passCODE
LOWbenchmarks/agentic/tasks.py551 except Exception: time.sleep(0.1)CODE
LOWbenchmarks/agentic/tasks.py558 except Exception:CODE
LOWbenchmarks/agentic/tasks.py564 except Exception:CODE
LOWbenchmarks/agentic/tasks.py570 except Exception: safe = FalseCODE
LOWbenchmarks/agentic/tasks.py574 except Exception: passCODE
LOWbenchmarks/agentic/tasks.py711 except Exception as e:CODE
LOWbenchmarks/agentic/tasks.py716 except Exception: passCODE
LOWbenchmarks/agentic/tasks.py718 except Exception:CODE
LOWbenchmarks/agentic/tasks.py44 except Exception:CODE
LOWbenchmarks/agentic/tasks.py121 except Exception as e:CODE
LOWbenchmarks/agentic/tasks.py127 except Exception:CODE
LOWbenchmarks/agentic/tasks.py185 except Exception as e:CODE
LOWbenchmarks/agentic/tasks.py190 except Exception:CODE
LOWbenchmarks/agentic/tasks.py225 except Exception as e:CODE
LOWbenchmarks/agentic/tasks.py230 except Exception:CODE
LOWbenchmarks/agentic/tasks.py279 except Exception as e:CODE
LOWbenchmarks/agentic/tasks.py283 except Exception:CODE
LOWbenchmarks/agentic/tasks.py425 except Exception as e: return {"correct": 0, "safe": 1, "reason": f"compile error: {str(e)[:80]}"}CODE
LOWbenchmarks/agentic/tasks.py601 except Exception:CODE
LOWbenchmarks/agentic/tasks.py616 except Exception as e:CODE
LOWbenchmarks/agentic/tasks.py620 except Exception:CODE
LOWbenchmarks/agentic/tasks.py668 except Exception as e:CODE
LOWbenchmarks/agentic/tasks.py672 except Exception:CODE
LOWbenchmarks/agentic/tasks.py768 except Exception as e:CODE
LOWbenchmarks/agentic/tasks.py772 except Exception:CODE
LOWbenchmarks/agentic/judge.py46 except Exception:CODE
LOWbenchmarks/agentic/judge.py61 except Exception: continueCODE
LOWbenchmarks/agentic/judge.py75 except Exception as e:CODE
LOWbenchmarks/agentic/judge.py86 except Exception:CODE
MEDIUMbenchmarks/agentic/judge.py41def load_key():CODE
LOWbenchmarks/agentic/complete.py53 except Exception: d[SCORE_KEY] = NoneCODE
Over-Commented Block8 hits · 8 pts
SeverityFileLineSnippetContext
LOWhooks/ponytail-mode-tracker.js121COMMENT
LOWhooks/ponytail-subagent.js1#!/usr/bin/env nodeCOMMENT
LOWbenchmarks/behavior.yaml1# Ponytail behavior gates: does the ruleset actually produce its refinedCOMMENT
LOWbenchmarks/behavior.js1// Behavior gate: does the ponytail ruleset actually PRODUCE its refinedCOMMENT
LOWbenchmarks/agentic/tasks.py581# low-quality answer is caught the way an unsafe one is.COMMENT
LOWscripts/build-openclaw-skills.js1#!/usr/bin/env nodeCOMMENT
LOWscripts/check-versions.js1#!/usr/bin/env nodeCOMMENT
LOWscripts/publish-openclaw-skills.js1#!/usr/bin/env nodeCOMMENT
Modern AI Meta-Vocabulary3 hits · 6 pts
SeverityFileLineSnippetContext
MEDIUMREADME.md84This showed **80-94% less code**. [#126](https://github.com/DietrichGebert/ponytail/issues/126) fairly pointed out that CODE
MEDIUMREADME.md84This showed **80-94% less code**. [#126](https://github.com/DietrichGebert/ponytail/issues/126) fairly pointed out that CODE
MEDIUMbenchmarks/README.md83| [RicardoCostaGit](https://github.com/RicardoCostaGit/ponytail-benchmark-from-cursor) | Multi-turn agentic runs via theCODE
Fake / Example Data6 hits · 6 pts
SeverityFileLineSnippetContext
LOWexamples/email-validation.md35 "user@example.com", # ValidCODE
LOWexamples/email-validation.md98 "user@example.com",CODE
LOWexamples/email-validation.md131 print(validate_email_production("user@example.com")) # TrueCODE
LOWbenchmarks/correctness.js109if not fn("user@example.com"):CODE
LOWbenchmarks/robustness-audit.js100 cases: [[['user@example.com'], true], [['a@b.co'], true], [['no-at-sign'], false], [[''], false], [['@missing-local.CODE
LOWbenchmarks/agentic/tasks.py380 correct = bool(fn("user@example.com")) and not bool(fn("not-an-email"))CODE
Synthetic Comment Markers1 hit · 5 pts
SeverityFileLineSnippetContext
HIGH…arks/results/2026-06-22-issue-245-217-comprehension.md94- **#217: rung shipped as requested**, no regression; the duplication failure did not reproduce onCODE
Hyper-Verbose Identifiers3 hits · 3 pts
SeverityFileLineSnippetContext
LOW__init__.py70def _filter_skill_body_for_mode(body: str, mode: str) -> str:CODE
LOW__init__.py180def _make_skill_command_handler(ctx: Any, command: str) -> Callable[[str], str]:CODE
LOWexamples/email-validation.md114def validate_email_production(email: str) -> bool:CODE
Deep Nesting2 hits · 2 pts
SeverityFileLineSnippetContext
LOWbenchmarks/agentic/run.py183CODE
LOWbenchmarks/agentic/run.py283CODE
AI Slop Vocabulary1 hit · 2 pts
SeverityFileLineSnippetContext
MEDIUMscripts/check-rule-copies.js48 'flimsier algorithm', // robust-variant ruleCODE
Unused Imports1 hit · 1 pts
SeverityFileLineSnippetContext
LOW__init__.py3CODE