SkillFab

A skill for designing, validating, and analyzing survey instruments in social science research. Features: generate Likert items from construct definitions, expert content validity checklist, pilot study item analysis (discrimination, item-total correlation, floor/ceiling effects), EFA/CFA with fit indices, reliability analysis (alpha, omega, test-retest ICC), measurement invariance testing, common method bias diagnostics. Outputs validated scale table, factor loading diagram, reliability report, final questionnaire .docx. For psychology, sociology, education, and management researchers.

A skill for conducting reflexive thematic analysis of qualitative data (interview transcripts, field notes, open-ended survey responses). Features: ingest .txt/.docx/.csv files, auto-generate initial open codes using semantic similarity, cluster codes into candidate themes via hierarchical clustering, interactive theme refinement, structured codebook generation with theme definitions and example quotes, thematic map visualization. Follows Braun & Clarke reflexive TA framework. Outputs: codebook .csv, coded excerpts .xlsx, thematic network .png, methods-section draft .md.

A skill that analyzes public discourse frames on social media (Weibo, Twitter/X, Reddit) using framing theory from political communication and sociology. Features: scrape posts by keyword/hashtag/time range, detect dominant frames using Entman 1993 four-function model (problem definition, causal attribution, moral evaluation, treatment recommendation), classify into episodic vs thematic / gain vs loss / human interest vs conflict frames, stance and sentiment analysis per frame, temporal frame evolution tracking, frame co-occurrence network visualization. For social movement research, political communication, public opinion analysis, and media studies.

A skill for processing classical Chinese (wenyanwen) texts: automatic punctuation restoration for raw unpunctuated texts, classical Chinese-specific word segmentation, named entity recognition for historical figures/places/official titles/reign periods, parallel translation alignment between classical and modern Chinese/English, and KWIC concordance search. Uses SikuBERT or GuwenBERT. For digital humanities researchers, historians working with dynastic histories, and philosophy researchers working with pre-Qin texts.

A skill that extracts structured policy variables from Chinese government policy documents (gov.cn and local government websites) for use in causal inference designs (DID, Event Study, RDD). ## Core Workflow 1. **Policy Discovery**: Search and crawl government websites for policies matching user-defined keywords, date ranges, and administrative levels (national/provincial/municipal) 2. **Policy Variable Extraction**: From each policy document, extract: - Policy intensity (scope, enforcement level, funding amount) - Effective date / announcement date / implementation deadline - Affected groups (industry, region, demographic) - Policy type (regulation, subsidy, tax incentive, quota, ban) 3. **Treatment Assignment Table**: Generate a ready-to-use panel dataset with: - `policy_id`, `policy_name`, `announce_date`, `effective_date` - `intensity_score` (continuous, 0-1 normalized) - `affected_regions` (province/city/prefecture codes) - `affected_industries` (GB/T industry codes) - `treatment_dummy` (binary coding suitable for DID staggered adoption) 4. **Integration**: Output directly as Stata .dta / R .rds / CSV, with optional DID/Event Study .do or .R template ## Technical Requirements - Web scraping for gov.cn and provincial government sites (respect rate limits) - NLP pipeline: Chinese text segmentation (jieba), keyword extraction (TF-IDF/TextRank), policy intensity scoring via pre-trained Chinese BERT - Dated policy identification using regex patterns for Chinese date formats - built-in government policy taxonomy for industry/region coding ## Inputs - Keywords or policy topic (e.g., "新能源汽车补贴", "房地产调控") - Date range - Administrative level filter - Output format preference ## Outputs - Structured policy database (CSV/Parquet) - Treatment assignment panel (Stata .dta + R .rds + CSV) - DID/Event Study starter template (.do + .R) - Policy discovery log with source URLs ## Dependencies - Python 3.10+, jieba, transformers, requests, beautifulsoup4, pandas - Optional: Stata/R for template generation

Multi-tool AI session data analyzer

safe-physical-os-boot

Use when preparing, executing, observing, or diagnosing an OS/kernel boot on physical development hardware through firmware, a bootloader, or serial transport, especially when emulator evidence, artifact identity, recovery availability, one-shot boot commands, or early-boot silence must be handled safely.

build-interactive-paper-maps

Design, implement, and debug publication-ready interactive research architecture maps for technical blogs and research notes. Use when Codex needs to organize related papers by mathematical role, turn a static architecture diagram into clickable HTML/SVG, map citations onto a non-serial topology, distinguish pipeline factorization from CNN/Transformer backbones and diffusion/flow inference semantics, or integrate and validate such a figure in Markdown, Jekyll, or GitHub Pages.

build-interactive-diagrams

Build polished, self-contained interactive HTML/SVG diagrams from nodes, edges, views, descriptions, and links. Use when Codex needs to create a clickable architecture diagram, flowchart, system map, research map, or technical-blog figure that works in a browser without a frontend framework.

concept-gap-digest

Use when a user wants to analyze local AI assistant session history for concepts, terms, jargon, APIs, or mental models they asked AI to explain, then produce a privacy-safe knowledge-gap digest, review plan, or recurring learning backlog without sharing raw transcripts.

agent-work-insight

Use when a user wants to analyze local AI coding assistant session patterns and turn aggregate focus, friction, and repeated workflows into SkillFab skill request drafts without sharing raw transcripts.