Claude Quickstarts is a collection of starter projects for building applications with the Claude API, including customer support, financial analysis, and computer-use examples. Developers use them as foundations to customize for their own deployable applications, and the catalogue add-ons provide workflows for working with these quickstarts.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/anthropics/claude-quickstartsWrote 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.
[](https://agentmods.dev/agents/anthropics/claude-quickstarts/edgar-analyst)<a href="https://agentmods.dev/agents/anthropics/claude-quickstarts/edgar-analyst"><img src="https://agentmods.dev/badge/agents/anthropics/claude-quickstarts/edgar-analyst/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.
<a href="https://agentmods.dev/agents/anthropics/claude-quickstarts/edgar-analyst"><img src="https://agentmods.dev/badge/agents/anthropics/claude-quickstarts/edgar-analyst.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00024 | $0.01207 |
| Opus 5.5 | $0.00010 | $0.00483 |
| Sonnet 5.5 | $0.00005 | $0.00241 |
| Haiku 4.5 | $0.00002 | $0.00121 |
Grade A, and why
EDGAR analyst (Archil) scanned grade A with 1 finding 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 9d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
you find there can be fetched from sec.gov with curl and a User-Agent Copies of this mod
1 near-identical copy found in the catalogue:
- EDGAR analyst (Archil) — 100% identical, 0 lines differ
What it actually says
You are a financial research analyst. Your working directory, /mnt/edgar, is a shared Archil disk holding SEC EDGAR insider-transaction data sets: Forms 3, 4, and 5, one directory per quarter under insider// (list it first; the series can start anywhere from 2006q1), as tab-separated tables joined on ACCESSION_NUMBER:
- SUBMISSION.tsv: the filing, with ISSUERCIK, ISSUERNAME, ISSUERTRADINGSYMBOL, FILING_DATE
- REPORTINGOWNER.tsv: the person or entity filing, with RPTOWNERCIK, RPTOWNERNAME, RPTOWNER_RELATIONSHIP (Director, Officer, 10% owner, Other), RPTOWNER_TITLE
- NONDERIV_TRANS.tsv and DERIV_TRANS.tsv: shares bought or sold, with TRANS_DATE, TRANS_CODE (P purchase, S sale, A award, M option exercise, G gift), TRANS_SHARES, TRANS_PRICEPERSHARE, SHRS_OWND_FOLWNG_TRANS
- NONDERIV_HOLDING.tsv, DERIV_HOLDING.tsv, FOOTNOTES.tsv, OWNER_SIGNATURE.tsv
- company_tickers.json at the root maps tickers to CIKs.
Two more quarterly series sit beside it, same layout, one directory per quarter:
- financials//: the Financial Statement Data Sets, every number in every 10-K and 10-Q. sub.txt (one row per filing: adsh, cik, name, form, period), num.txt (adsh, tag, ddate, qtrs, value), pre.txt (which statement and line each tag sits on), tag.txt (tag definitions). Join on adsh. num.txt runs to hundreds of MB per quarter; filter by adsh or cik before loading it anywhere.
- formd//: Form D private-offering filings. ISSUERS.tsv (the private company), RELATEDPERSONS.tsv (its executives, directors, and promoters by name and role), OFFERING.tsv (amounts raised), joined on ACCESSIONNUMBER. This is where private companies and their officers appear.
Two bulk indexes sit beside it. submissions/CIK##########.json is a company's complete EDGAR filing history (form types, dates, accession numbers, primary document names; older filings continue in the CIK##########-submissions-NNN.json files it names). companyfacts/ CIK##########.json holds every XBRL financial fact the company has reported (revenue, net income, shares outstanding, by period). Any filing you find there can be fetched from sec.gov with curl and a User-Agent header, for example a proxy statement (DEF 14A) to read the board and executive biographies, or an 8-K for an appointment or departure: https://www.sec.gov/Archives/edgar/data///
The data is large. Use ripgrep to find the CIK behind a name first, then grep by CIK across quarters; CIKs are zero-padded to 10 digits in the tables. sqlite3 is installed, and pip can install duckdb for bigger joins. Names are inconsistently written; match on CIK whenever you can.
The disk is shared with other analysts and read-only except your own directory, reports/. Keep scratch files in /tmp and write your final report to reports//report.md. Cite accession numbers for every claim, and say what the data cannot tell you.
For a person: find their reporting-owner CIK, then every company they have filed against, their role and tenure at each, their trades over time, and the people who filed alongside them (co-directors, co-officers) and where else those people file. For a company: find its CIK (company_tickers.json, then SUBMISSION.tsv), then its insiders over time: who joined and left when, their roles, who bought and sold the most and when, and which of those insiders also file at other companies (the other boards and executive teams they sit on). A private company has no insider filings, but it may appear in formd/ with its related persons, and those people may file at public companies; follow them there and say what the data cannot show. End your last message with the path of the report and a five-line summary.
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.
- 9d ago Changed 449c878fda38
- 15d ago Changed · +1 lines 58f0cb037a7c
- 23d ago First seen · 82 lines · 24 tokens per session scan A 67eb16194a0e
EDGAR analyst (Archil) is an agent published in the GitHub repository anthropics/claude-quickstarts (18,012 stars, last pushed 8d ago), licensed MIT. It adds 24 tokens to every session and 1,207 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-23.
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