Regulations.gov Comments — Full-Text Extractor avatar

Regulations.gov Comments — Full-Text Extractor

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Regulations.gov Comments — Full-Text Extractor

Regulations.gov Comments — Full-Text Extractor

Extract the FULL TEXT of public comments on US federal rulemaking dockets from Regulations.gov — not just metadata. Get who is arguing for or against a rule, in their own words. Filter by docket, search term, or date. Zero-config returns recent comments with body text. Official US gov API.

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Bikram

Bikram

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4 days ago

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Extract the full text of public comments submitted on U.S. federal rulemaking dockets, straight from the official Regulations.gov API v4. When a federal agency proposes a rule, the public — companies, trade associations, advocacy groups, individuals — files comments arguing for or against it. This actor pulls those comments and, crucially, the actual words people wrote, not just the titles.

Run it with zero configuration to get recent comments (last 30 days) complete with their body text.

The wedge — body text, not just metadata

Every other Regulations.gov scraper and the API's own /comments list endpoint return metadata only: comment id, agency, posted date, and a title like "Comment from Anonymous." The thing you actually want — what the comment says — is hidden behind a separate per-comment detail call.

This actor makes that detail call for you. For each comment it fetches /comments/{id}, reads attributes.comment, decodes the HTML entities, and hands you clean plain text. That is the entire differentiator: you get the argument, the citation, the lobbying position — in the commenter's own words.

Why this matters

Public comments are the raw material of regulatory intelligence:

  • Government affairs & lobbying — see exactly which firms and trade groups are arguing for or against a proposed rule, and what they're claiming, before the final rule drops.
  • Legal & compliance — read the substantive objections to a rule to anticipate litigation angles and the agency's likely response in the final rule.
  • Policy research & journalism — quantify support vs. opposition, surface mass-comment campaigns, quote real submissions.
  • Competitive intelligence — track when competitors file comments and what positions they take on rules that affect your industry.
  • AI / LLM pipelines — feed full comment text into summarization, stance detection, or entity extraction over MCP.

Input

Every field is optional. Empty input {} returns recent comments (last 30 days) with body text.

FieldTypeDefaultDescription
searchTermstring""Full-text search across comments, e.g. menthol cigarettes. Blank = most recent comments across all dockets.
docketIdstring""Restrict to one rulemaking docket, e.g. FDA-2025-P-7321. Cross-sells with the Federal Register Monitor actor, which outputs docketIds.
postedAfterstring30 days agoOnly comments posted on or after this YYYY-MM-DD date.
fetchBodybooleantrueThe differentiator. ON = one extra request per comment to pull the real body text. OFF = metadata only (faster, no per-comment calls).
apiKeystringDEMO_KEYRegulations.gov API key. DEMO_KEY works with no signup but is rate-limited. See below.
maxCommentsinteger50Max comments to output. Kept low because DEMO_KEY is rate-limited and each body needs its own request.

Zero-config (recent comments, last 30 days, with body text)

{}

By docket (everything filed on one rule)

{ "docketId": "FDA-2025-P-7321", "maxComments": 200 }

By topic

{ "searchTerm": "net neutrality", "postedAfter": "2026-01-01", "maxComments": 100 }

The default DEMO_KEY works with no signup, but it shares a heavily-used, low rate-limit bucket (only a handful of requests per hour). Because fetching each comment body costs one request, DEMO_KEY runs are best kept small — and the actor will warn you and suggest a key if it hits the limit (HTTP 429), returning whatever it managed to fetch.

To unlock 1,000 requests/hour:

  1. Go to api.data.gov/signup and enter your name + email.
  2. The key is emailed instantly — no approval wait, no cost.
  3. Paste it into the apiKey input.

That's enough to pull hundreds of full-text comments per run.

Output

One dataset item per comment:

FieldTypeDescription
commentIdstringRegulations.gov comment/document id, e.g. FDA-2025-P-7321-3668.
docketIdstring | nullParent rulemaking docket id.
documentIdstring | nullThe comment's own document id (same as commentId).
agencyIdstring | nullIssuing agency acronym, e.g. EPA, FDA, FTC.
titlestring | nullComment title (often Comment from <name>).
postedDatestring | nullISO date the comment was posted.
receivedDatestring | nullISO date the agency received it.
commentTextstring | nullThe actual comment body, HTML-decoded to plain text.
submitterNamestring | nullFirst Last when the submitter provided it.
organizationstring | nullSubmitter's organization, when provided.
govAgencyTypestring | nullGovernment agency type, when the submitter is a gov body.
attachmentUrlsstring[]URLs to PDF/doc attachments. URLs only — contents are not downloaded.
withdrawnboolean | nullWhether the comment was withdrawn.
commentUrlstringPublic Regulations.gov page for the comment.
scrapedAtstringISO-8601 UTC timestamp of extraction.

Missing values are null — never fabricated.

What this actor is NOT

  • It does not download or parse PDF/Word attachment contents. When a comment is just "See attached file(s)," the text is in a PDF — this actor gives you the attachmentUrls so you can fetch them yourself, but it does not OCR or extract them.
  • It is not a private database. Everything it returns is public record published by the U.S. federal government on Regulations.gov. It performs no scraping, login, or circumvention — only authenticated calls to the official API.
  • It does not post, submit, or modify comments. Read-only.

Source

Official U.S. government data via the Regulations.gov API v4 (https://api.regulations.gov/v4/). Public rulemaking comments are federal public records.

Pairs well with

  • Federal Register Monitor — surfaces new proposed rules and their docketIds; pipe those docketIds into this actor to read what the public is saying about each one.