ai-asset-pricing: Skill for Claude Code

.claude/skills/new-project/SKILL.md

new-project is a skill for Claude Code from Alexander-M-Dickerson/ai-asset-pricing. It costs 41 tokens per session (1,861 once invoked), scanned A, original, MIT.

A project generator for empirical finance research. It creates a standard folder structure with LaTeX paper files, code, scripts, results, literature, guidance notes, and project instructions.

In plain words
What is it for?
Use it to start a new research project with a valid name and optional description. It prepares the initial paper and repository structure without overwriting an existing project.
Why use it?
It saves time setting up repeated project files and gives the work a consistent place for analysis, writing, and supporting material.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: mentions CLAUDE.md; names the AskUserQuestion tool.

This is Alexander-M-Dickerson/ai-asset-pricing's own configuration. It tells Claude Code how to work on ai-asset-pricing 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 ai-asset-pricing configures →

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is - Reference results: `../results/figures/`, `../results/tables/`.

Reuse

Borrowing it

Nothing to install: this file belongs to Alexander-M-Dickerson/ai-asset-pricing. 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/Alexander-M-Dickerson/ai-asset-pricing/main/.claude/skills/new-project/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/Alexander-M-Dickerson/ai-asset-pricing

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for new-project

README.md
[![agentmods](https://agentmods.dev/badge/skills/alexander-m-dickerson/ai-asset-pricing/new-project/github.svg)](https://agentmods.dev/skills/alexander-m-dickerson/ai-asset-pricing/new-project)
Your own site
<a href="https://agentmods.dev/skills/alexander-m-dickerson/ai-asset-pricing/new-project"><img src="https://agentmods.dev/badge/skills/alexander-m-dickerson/ai-asset-pricing/new-project/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for new-project

Your own site · 80×15
<a href="https://agentmods.dev/skills/alexander-m-dickerson/ai-asset-pricing/new-project"><img src="https://agentmods.dev/badge/skills/alexander-m-dickerson/ai-asset-pricing/new-project.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,861 The whole file, excluding the scripts and references it only reads on demand.
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 $0.00041 $0.01861
Opus 5 $0.00020 $0.00931
Sonnet 5 $0.00008 $0.00372
Haiku 4.5 $0.00004 $0.00186

Measured 12d ago against content hash d111e99d9df3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

new-project 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 12d 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/skills/new-project/SKILL.md · 246 lines

How it starts

The opening of the file, as written. The whole thing — 246 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Create New Research Project

Four phases: Validate → Gather Context → Create Scaffold → Setup Paper.

Examples

  • /new-project momentum_replication -- create project with name only
  • /new-project vol_surface "Implied volatility surface dynamics" -- name + description
  • /new-project bond_liquidity -- another example

Phase 1: Validate Input

Parse $ARGUMENTS:

  • First token = project name
  • Remaining tokens (if any) = optional description text

If $ARGUMENTS is empty, use AskUserQuestion to ask:

"What should the project be called? Use lowercase with underscores (e.g., momentum_replication, vol_surface, bond_liquidity)."

Validation rules:

  • Must match regex: ^[a-z][a-z0-9_]{1,49}$ (lowercase, underscores only, starts with letter, 2-50 chars)
  • Reject Windows-reserved names: con, prn, aux, nul, com1-com9, lpt1-lpt9
  • If invalid, explain the rules, show examples, and re-ask

Collision check:

  • If projects/<name>/ already exists, ask the user: "Project <name> already exists. Do you want to open it, or choose a different name?"
  • Do NOT overwrite existing projects

Phase 2: Gather Context

If no description was provided in $ARGUMENTS, use a single AskUserQuestion with these questions:

  1. "Brief description of the project (1-2 sentences):"
  2. "Which WRDS databases will this project use? (e.g., CRSP, OptionMetrics, Compustat, TAQ, Bonds, JKP)"
  3. "Any initial methodology notes or reminders for this project?"

If a description WAS provided in $ARGUMENTS, still ask questions 2 and 3.

Store the answers for template filling.

Phase 3: Create Scaffold

3a. Create directories

Run a single Bash command:

mkdir -p projects/<name>/{latex,code,scripts/tests,results/{figures,tables},literature,guidance,_misc}

3b. Write project README.md

Use the Write tool to create projects/<name>/README.md:

# {Project Name in Title Case}

{User's description}

## Status

- [ ] Data sourced
- [ ] Exploratory analysis complete
- [ ] Main results produced
- [ ] Write-up drafted
- [ ] Write-up finalized

## Data Dependencies

This project uses datasets from the global `data/` folder:

| Dataset | Description | Status |
|---------|-------------|--------|
| *(to be filled as data is fetched)* | | |

## Structure

| Folder | Purpose |
|--------|---------|
| `latex/` | LaTeX writeup |
| `code/` | Production code (clean, reusable) |
| `scripts/tests/` | Exploratory investigations (each in own subfolder with `output/`) |
| `results/` | Publication-ready figures and tables |
| `literature/` | Reference papers |
| `guidance/` | Methodology notes |
| `_misc/` | Catch-all |

## Notes

- Created: {today's date, YYYY-MM-DD}
- WRDS databases: {databases}

Read the full file on GitHub · 246 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. 12d ago First seen · 246 lines · 41 tokens per session scan A d111e99d9df3

Subscribe to this mod's changes

new-project is a skill published in the GitHub repository Alexander-M-Dickerson/ai-asset-pricing (59 stars, last pushed 4mo ago), licensed MIT. It adds 41 tokens to every session and 1,861 once invoked, about $0.0002 per session on Opus 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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens