ai-asset-pricing

Plugin ai-asset-pricing from marketplace fin-skills in howard-lynn-ye/fin-skills. Commands read from the repo's manifest — 1 month ago.

Skills (38)

• audit-captions

  Audit all table and figure captions for language, notation, and formatting consistency

• audit-math

  Adversarial audit of mathematical proofs, derivations, and formal environments

• audit-section

  Deep audit of a single section -- style, factual accuracy, citations, logical flow

• bond-data

  Reference for the Dickerson corporate bond dataset: column mappings between WRDS and PyBondLab, rating encoding, return definitions, signal clusters, and data gotchas. Auto-apply when loading bond data for PyBondLab analysis.

• build-context

  Generate guidance/paper-context.md from user-provided .tex, .md, or .pdf files

• build-deck

  Create and compile Beamer presentations following the Rhetoric of Decks philosophy. Use when making seminar or conference slides.

• build-paper

  Compile LaTeX to PDF using pdflatex + bibtex cycle

• check-consistency

  Fast cross-section consistency scan for numbers, terminology, and references

• compare-versions

  Show diff between current and proposed text with change rationale

• create-audit-agent

  Creates new Claude Code agent configuration files or audits existing ones in .claude/agents/. Validates frontmatter, routing keywords, body-frontmatter alignment, ecosystem integration, and cross-agent consistency using a 17-point checklist.

• create-skill

  Creates new Claude Code skills, auto-apply skills, or auto-trigger rules, or audits existing ones for quality and effectiveness.

• edit-section

  Revise an existing section for style, clarity, and correctness

• extract-section

  Extract a section from main.tex by key name

• factor-construction

  Look-ahead bias prevention and portfolio formation rules for cross-sectional asset pricing factors. Covers signal timing, portfolio sorts, return alignment, and rebalancing conventions. Auto-apply when constructing factors, sorting stocks into portfolios, or computing long-short returns.

• full-paper-audit

  Audit the entire paper -- cross-section consistency, all citations, all style issues

• idea

  Adversarial research idea generator for empirical asset pricing. Surveys literature via Perplexity, stress-tests hypotheses, maps WRDS data feasibility, and compiles a research plan skeleton. Use when brainstorming new paper ideas, sharpening existing hypotheses, or resuming a prior ideation session

• latex-doctor

  Clean and fix .tex files -- strip comments, fix compilation errors, verify section markers

• new-project

  Create a new empirical research project: generates projects/<name>/ with latex, code, scripts, results, literature, and guidance subfolders plus README.md and project-level CLAUDE.md.

• onboard

  Agent-driven cold-start onboarding. Use the repo shell entrypoint to find or install Python 3.11+, then run the shared bootstrap audit/plan/apply flow and configure WRDS only if the user has it.

• outline

  Analyze paper structure — section balance, word counts, Cochrane-principle compliance

• panel-data-rules

  Rules and gotchas for CRSP, Compustat, and financial panel data: safe lagging/leading with date gap checks, look-ahead bias prevention, CCM linking, book equity construction, and missing value conventions. Auto-apply when working with CRSP, Compustat, or financial panel data.

• proofread

  Mechanical error scan -- typos, LaTeX formatting, punctuation, spacing

• publication-figures

  Publication-ready figure conventions for empirical finance and economics. Covers matplotlib styling, color palettes, export settings, and common figure types (time series, decile bars, coefficient plots, event studies). Auto-apply when creating any figure, plot, or visualization.

• pybondlab-report

  Generates structured results reports after PyBondLab portfolio formation runs. Auto-apply when running StrategyFormation, BatchStrategyFormation, BatchWithinFirmSortFormation, or any portfolio sorting with PyBondLab.

• research

  Search for academic papers, references, and methodology literature using Perplexity MCP

• respond-to-referee

  Draft response letter text and LaTeX edits for referee points, or generate a complete reply document

• rule-create

  Creates new .claude/rules/ files following best practices, or audits existing rules for quality and effectiveness.

• run

  Fast batch/single portfolio sort on Dickerson bond data. Bypasses orchestrator agent — runs directly via Bash. Use for known workflows on real data. Examples: /run batch cs ytm bbtm, /run batch cs ytm --wfs, /run single cs --nport 10

• setup-paper

  Scaffolds a new academic paper from the LaTeX boilerplate template. Copies template files, replaces placeholder tokens with user-provided title, authors, and affiliations, writes [REMOVE]-tagged filler content with Fama-French citations, and compiles a test PDF. Use when starting a new paper or crea

• split-pdf

  Download, split, and deeply read academic PDFs with adaptive chunking. Splits into optimally-sized chunks based on paper length, reads in controlled batches, and produces structured extraction notes tailored for empirical finance papers.

• style-check

  Analyze LaTeX text for violations of academic writing standards

• submission-prep

  Pre-submission checklist for JF, RFS, JFE, or other target journals

• sync-context

  Detect documentation drift and propose updates to docs/ai/, AGENTS.md, and CLAUDE.md. Use when session-start warnings flag stale docs, after significant code changes, or periodically to keep context current.

• verify-citations

  Audit citations in LaTeX files -- check all \cite keys exist in .bib and verify via Perplexity

• wrds-psql

  Use this skill when the user needs to query WRDS data via PostgreSQL from the local machine. Covers psql connection using .pgpass credentials, query execution patterns, CSV/parquet export, and best practices for large extractions. Invoke when the user wants to pull data from WRDS (CRSP, OptionMetric

• wrds-schema

  Use this skill at the start of a session when working with WRDS data (CRSP, OptionMetrics, Compustat, TAQ). It pre-loads schema knowledge — table names, column names, join keys, data types, and common gotchas — so you can write correct queries without exploratory round-trips. Invoke when the user me

• wrds-ssh

  This skill should be used when the user needs to connect to WRDS servers, run SAS code on WRDS, execute SQL queries on WRDS PostgreSQL, submit batch jobs to WRDS, or transfer files to/from WRDS. Use this skill whenever WRDS server access is required for data extraction, processing, or analysis.

• write-section

  Write a new section or subsection of an empirical finance paper following academic writing rules

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