What is taq-wrds-expert?

A research assistant for NYSE Trade and Quote data on WRDS, a service that provides financial research databases. It extracts tick-level trades, quotes, best available prices, and related market measures using SSH, SAS, and PostgreSQL.

Use it to calculate measures such as five-minute realized variance, bid-ask spreads, trade statistics, quote statistics, and filtered stock-market samples.

It helps researchers work with very large, detailed market records without having to learn the dataset’s file layout and filtering rules first.

How Alexander-M-Dickerson/ai-asset-pricing configures Claude Code

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/agents/taq-wrds-expert.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.

README.md

[![agentmods](https://agentmods.dev/badge/agents/alexander-m-dickerson/ai-asset-pricing/taq-wrds-expert/github.svg)](https://agentmods.dev/agents/alexander-m-dickerson/ai-asset-pricing/taq-wrds-expert)

Your own site

<a href="https://agentmods.dev/agents/alexander-m-dickerson/ai-asset-pricing/taq-wrds-expert"><img src="https://agentmods.dev/badge/agents/alexander-m-dickerson/ai-asset-pricing/taq-wrds-expert/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.

Your own site · 80×15

<a href="https://agentmods.dev/agents/alexander-m-dickerson/ai-asset-pricing/taq-wrds-expert"><img src="https://agentmods.dev/badge/agents/alexander-m-dickerson/ai-asset-pricing/taq-wrds-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 322 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 6,298 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.

Model	Per session	Once invoked
Fable 5.1	$0.00322	$0.06298
Opus 5.5	$0.00129	$0.02519
Sonnet 5.5	$0.00064	$0.01260
Haiku 4.5	$0.00032	$0.00630

Measured 2mo ago against content hash 3cc70780ba15, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

taq-wrds-expert 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/agents/taq-wrds-expert.md · 507 lines

How it starts

The opening of the file, as written. The whole thing — 507 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an expert agent for extracting and processing NYSE Trade and Quote (TAQ) data on WRDS. You have deep knowledge of the TAQ database structure, efficient programming techniques, and data extraction strategies for empirical finance research.

Before running any psql query, invoke the wrds-psql skill to load connection patterns and formatting rules.

WRDS TAQ Directory Layout (verified 2026-02-27)

All TAQ data lives under /wrds/nyse/sasdata/, with a legacy alias at /wrds/taq/sasdata/.

/wrds/nyse/sasdata/
    taqms/                      # TAQ Millisecond raw data (2003-present)
        ct/                     # Trades: ctm_YYYYMMDD.sas7bdat
        cq/                     # Quotes: cqm_YYYYMMDD.sas7bdat
        nbbo/                   # NBBO: nbbom_YYYYMMDD.sas7bdat + ix_nbbom_YYYYMMDD
        mast/                   # Master: mastm_YYYYMMDD.sas7bdat (starts 2009-02-25, NOT 2003)
        nbbod2m/                # NBBO daily-to-monthly: nbbod2m_YYYYMMDD (starts 2015-01-02)
        luld_ct/                # LULD trade halts: luld_ctm_YYYYMMDD (starts 2018-01-02)
        luld_cq/                # LULD quote halts: luld_cqm_YYYYMMDD (starts 2018-01-02)
    taqs/                       # Legacy monthly (1993-2014, but ends 2014-07-31 — incomplete)
    wrds_taqms_nbbo/            # WRDS-computed NBBO: complete_nbbo_YYYYMMDD (2003-present)
    wrds_taqms_wct/             # WRDS Consolidated Trades: wct_YYYYMMDD (2003-present)
    wrds_taqms_iid/             # WRDS Intraday Indicators: wrds_iid_YYYY (2003-present, annual)
    wrds_taqs_ct/               # WRDS Consolidated Trades, legacy: wct_YYYYMMDD (1993-2014)
    wrds_taqs_nbbo/             # WRDS-computed NBBO, legacy: nbbo_YYYYMMDD (1993-2014)
    wrds_taqs_iid_v1/           # WRDS Intraday Indicators v1, legacy: wrds_iid_YYYY (1993-2014)

/wrds/taq/sasdata/              # Legacy monthly (1993-01-04 through 2014-12-31) — COMPLETE range
                                # Contains ct_YYYYMMDD, cq_YYYYMMDD

Read the full file on GitHub · 507 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.

2mo ago First seen · 507 lines · 322 tokens per session scan A 3cc70780ba15

Subscribe to this mod's changes

taq-wrds-expert is an agent published in the GitHub repository Alexander-M-Dickerson/ai-asset-pricing (59 stars, last pushed 6mo ago), licensed MIT. It adds 322 tokens to every session and 6,298 once invoked, about $0.0013 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.

Finance and fintech Research

taq-wrds-expert next to 6 agents from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
taq-wrds-expertAlexander-M-Dickerson/ai-asset-pricing	Agent	59	6mo ago	MIT	A	322	Claude Code
ic-challengermariourquia/cre-skills-plugin	Agent	51	9d ago	none	A	85	Claude Code
token-economics-designerMatt-Dionis/claude-code-configs	Agent	619	1y ago	MIT	A	28	Claude Code
soleur-finance-budget-analystjikig-ai/soleur	Agent	21	today	none	A	78	Claude Code
pm-business-analystgeekatron/jerry	Agent	37	5d ago	none	B	107	Claude Code
financial-integrity-auditorblendsdk/claude-codeops	Agent	4	3mo ago	MIT	A	142	Claude Code
royalty-audit-analystrecoupable/skills	Agent	9	today	none	A	46	Claude Code

ai-asset-pricing: Agent for Claude Code