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presentation-signals

wanshuiyin/Anti-AutoresearchSkill

Checkable-ish surface presentation signals a reviewer notices first — duplicate/near-identical tables, leftover pipeline/template strings, too-few or LLM-looking figures, and page-padding. AUXILIARY ONLY and weak by design: a deterministic pass (tools/check_presentation.py — dup-table + pipeline-artifact) plus a fresh cross-model GROSS-cases-only semantic pass (thin-float, LLM-figure, page-padding), every above-info finding span-anchored to the evidence ledger (claims.json). The adjudicator CAPS everything at minor (SURFACE_ONLY_SKILLS + SURFACE_PATTERNS) — these contribute at most SOFT_FLAGS,

Scanned · 1 to knowSkillSource: GitHub
165 stars +3 this week Updated 18d ago License MIT Context ≈155 tokens always loaded
60popular

Why this score

Stars9/35
Usage (forks)1/15
Upkeep25/25
License15/15
Owner history10/10

This repo hosts 10 skills, so its 165 stars are split between them (about 17 each) for scoring.

Popularity score: 60/100 from public GitHub signals only. It shows how widely used and maintained this is, not how well it works. Not included yet: the fake-star check. The security scan is shown separately and doesn't change the score. How we rank

Security

Scanned Oct 20, 2026 at commit 5f5d82421c75, with Cisco's open-source skill-scanner.

What its code does:

  • Runs shell commands Common for dev tools. Read the commands it runs.SKILL.md:237 and 1 more

A scan lists patterns in the code. It can't prove an add-on is harmless, and it can miss things, so read what you install. How we scan

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