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compound-science: Instructions file for Claude Code

CLAUDE.md

compound-science CLAUDE.md is an instructions file for Claude Code from James-Traina/compound-science. It costs 2,386 tokens per session, scanned A, original, MIT.

Repository instructions for the compound-science project, an AI-assisted research toolkit for quantitative social science. They describe a repeatable path from research ideas through planning, implementation, review, and reusable documentation.

In plain words
What is it for?
Use them to brainstorm research, create plans, run work with quality checks, request reviews from specialist perspectives, and save reusable research solutions.
Why use it?
They give contributors and coding assistants shared rules for organizing research work and checking its quality. Quantitative social science uses data and statistical methods to study social and economic questions.

Instructions file for Claude Code

Written for Claude Code: ${CLAUDE_PLUGIN_DATA} variable. Also seen: mentions .claude-plugin; mentions subagents; mentions Claude Code.

This is James-Traina/compound-science's own configuration. It tells Claude Code how to work on compound-science itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything compound-science configures →

not rated 14repo 7mo ago A scan 2,386 tokens original MIT
View source ↗ James-Traina/compound-science
Reuse

Borrowing it

Nothing to install: this file belongs to James-Traina/compound-science. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/James-Traina/compound-science/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/James-Traina/compound-science

Made for: Claude Code.

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Per session 2,386 This file is loaded in full into every session.
When invoked 2,386 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.02386 $0.02386
Opus 5.5 $0.00954 $0.00954
Sonnet 5.5 $0.00477 $0.00477
Haiku 4.5 $0.00239 $0.00239

Measured 2mo ago against content hash 1176edb736f0, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

compound-science CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

CLAUDE.md · 144 lines

How it starts

The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.

compound-science Plugin

AI-powered research tools for quantitative social science: structural econometrics, causal inference, game theory, applied micro, and reproducible pipelines. Built on the compound workflow principle: each unit of research work makes subsequent work easier.

Core Workflow

Brainstorm → Plan → Work → Review → Compound → Repeat

  1. /workflows:brainstorm — Explore research approaches, compare methods, pick one. Writes to docs/brainstorms/.
  2. /workflows:plan — Create an implementation plan from the brainstorm. Writes to docs/plans/.
  3. /workflows:work — Execute the plan with quality gates and convergence monitoring.
  4. /workflows:review — Multi-agent parallel review (econometric-reviewer, numerical-auditor, identification-critic, journal-referee).
  5. /workflows:compound — Extract reusable solutions into docs/solutions/ by category.

Each step has an interactive handoff offering the next step. Use /lfg to chain all five automatically, or /slfg for parallel swarm execution. Ideate (/workflows:ideate) is an optional divergent pre-step before brainstorming.

Skills (20)

Workflow (6) — core research loop

  • /workflows:ideate, /workflows:brainstorm, /workflows:plan, /workflows:work, /workflows:review, /workflows:compound

Chain (2) — automated multi-step execution

  • /lfg — Sequential: brainstorm → plan → work → review → compound (with hard gates)
  • /slfg — Parallel swarm variant of /lfg

Wrappers (2) — thin routing skills

  • /estimate — Routes to /workflows:work with estimation pipeline context from empirical-playbook
  • /replicate — Routes to reproducibility-auditor agent

Domain knowledge (10) — reusable reference skills

  • structural-modeling — NFXP, MPEC, BLP, dynamic discrete choice, auction models
  • causal-inference — IV/2SLS/GMM, DiD, RDD, synthetic control, matching
  • causal-ml — Double ML, causal forests (GRF), DR-Learner, post-LASSO, high-dimensional controls
  • game-theory — Nash/SPE/BNE equilibria, entry models, conduct testing, bargaining, multiple equilibria
  • identification-proofs — Formal identification arguments: target parameter → model → rank conditions → regularity conditions
  • bayesian-estimation — MCMC, Stan/PyMC/Numpyro, prior elicitation, MCMC diagnostics, Bayesian structural models
  • reproducible-pipelines — Makefile/Snakemake/DVC, Stata pipelines, environment management, replication standards
  • empirical-playbook — Method selection, diagnostics by method, power analysis, estimation pipeline, sensitivity analysis, data acquisition (FRED/World Bank)
  • publication-output — Publication-quality tables and figures: stargazer-style tables, event study plots, RD plots, specification curves
  • submission-guide — Pre-submission checklists, journal-specific formatting for 20+ journals, referee response strategy and templates

Read the full file on GitHub · 144 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2mo ago First seen · 144 lines · 2,386 tokens per session scan A 1176edb736f0

Subscribe to this mod's changes

compound-science CLAUDE.md is an instructions file published in the GitHub repository James-Traina/compound-science (14 stars, last pushed 7mo ago), licensed MIT. It adds 2,386 tokens to every session, about $0.0095 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

ResearchScientific
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