search-edgar-fulltext

sec.gov/search-edgar-fulltext-dpk6r2 · updated May 21, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$browse install sec.gov/search-edgar-fulltext-dpk6r2
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summary

Search the full body text of SEC EDGAR filings (10-K, 10-Q, 8-K, S-1, DEF 14A, 13F, 13D/G, Form 4, etc., 2001-present) via the public efts.sec.gov JSON API, with filters for form type, filer (CIK or name), filer location, SIC code, and date range. Returns structured filing metadata plus canonical filing-index and document URLs.

skill.md
name
search-edgar-fulltext
title
SEC EDGAR Full-Text Filing Search
description
>- Search the full body text of SEC EDGAR filings (10-K, 10-Q, 8-K, S-1, DEF 14A, 13F, 13D/G, Form 4, etc., 2001-present) via the public efts.sec.gov JSON API, with filters for form type, filer (CIK or name), filer location, SIC code, and date range. Returns structured filing metadata plus canonical filing-index and document URLs.
website
sec.gov
category
finance
tags
- sec - edgar - filings - full-text-search - regulatory - json-api
source
'browserbase: agent-runtime 2026-05-18'
updated
'2026-05-18'
recommended_method
api
alternative_methods
[]
verified
false
proxies
false

SEC EDGAR Full-Text Filing Search

Purpose

Search the full body text of every SEC EDGAR filing accepted electronically since 2001 — 10-K, 10-Q, 8-K, S-1, S-3, 424B*, DEF 14A, SC 13D, SC 13G, 13F-HR, Forms 3/4/5, N-PX, and dozens of others — for a phrase or boolean expression, and return a structured list of matching filings with filer identity, form type, filing date, period of report, business + incorporation state, SIC code, the canonical filing-index URL, and the direct URL to the matching exhibit. Read-only.

This is distinct from EDGAR's filing-metadata browse surface (/cgi-bin/browse-edgar), which lists filings by company without looking inside them. This skill searches the body text.

When to Use

  • "Find every 10-K from Q1 2024 that mentions 'climate risk'."
  • "Which 8-Ks from Apple in the last year contain 'material weakness'?"
  • "List all filings citing a specific Treasury regulation across the entire EDGAR corpus."
  • "Find SC 13D/G filings disclosing a stake above N% in {company}."
  • "Show all Form 4 trades by a named officer across every company they're an insider at."
  • Any flow where the question is "which filings mention X?" rather than "what filings did company Y submit?"

Workflow

EDGAR's full-text search is backed by a single public JSON endpoint: https://efts.sec.gov/LATEST/search-index (an AWS API Gateway in front of an OpenSearch/Elasticsearch cluster, accept-cors *, no auth, no cookies, no captcha). The consumer SPA at https://www.sec.gov/edgar/search/ is a thin jQuery wrapper that calls this exact endpoint and renders the same metadata fields. Always use the JSON endpoint directly — the browser path costs ~50× more agent turns and returns no extra data.

1. Build the query URL

GET https://efts.sec.gov/LATEST/search-index
    ?q=<phrase-or-boolean>
    [&forms=<csv>]
    [&dateRange=custom&startdt=YYYY-MM-DD&enddt=YYYY-MM-DD]
    [&ciks=<csv-of-10-digit-zero-padded>]
    [&entityName=<text>]
    [&locationCodes=<csv-of-state-codes>]
    [&locationType=located|incorporated]
    [&sics=<csv-of-4-digit-codes>]
    [&sort=desc|asc]
    [&from=N]

Headers:
  User-Agent: <YourOrg> <[email protected]>   # SEC fair-access courtesy
  Accept: application/json

The q parameter accepts:

  • A bare word: q=catastrophe
  • An exact phrase, URL-encoded with quotes: q=%22climate+risk%22 ("climate risk")
  • Boolean operators on plain or quoted terms: q=%22going+concern%22+AND+NOT+%22substantial+doubt%22. Supported operators: AND, OR, NOT, parentheses. Default operator between bare terms is AND.

Filter parameters and their semantics (every one verified live against the API on 2026-05-18):

ParamTypeMeaning
formscsvForm codes (10-K, 10-Q, 8-K, S-1, DEF 14A, SC 13D, SC 13G, 13F-HR, 4, 424B, N-PX, …). Matches the root formforms=10-K returns both 10-K and 10-K/A (verified). Multi-form: forms=10-K,8-K.
dateRangeenumMust be custom for startdt/enddt to take effect.
startdt / enddtYYYY-MM-DDBounds on file_date (the date the filing landed at EDGAR, not the period of report). Both inclusive.
cikscsv10-digit zero-padded CIK (e.g. 0000320193 for Apple, not 320193). Multi: 0000320193,0001652044. Filters to filings where the CIK appears in _source.ciks[] — i.e. filer or co-filer or insider-subject (Form 4).
entityNamestringFuzzy text match on the company/individual-name index. Multi-select in the UI; comma-separate to OR them. Useful when you only know the name. The API returns CIKs in the results — cache them and switch to ciks= for repeat queries (more precise).
locationCodescsv2-letter state code (CA, NY, …) or 2-char EDGAR foreign code (e.g. X0 = England). Plural form required — the singular locationCode= is silently ignored.
locationTypeenumlocated (default — matches _source.biz_states[], the filer's business-address state) or incorporated (matches _source.inc_states[], the state of incorporation).
sicscsv4-digit Standard Industrial Classification codes (e.g. 2834 pharma, 6022 state commercial banks, 7372 software). Multi-select supported.
sortenumdesc = file_date newest first, asc = oldest first. Omit for default relevance (_score) sort. The variants sortBy=date, order=date are silently ignored — only `sort=desc
fromintPagination offset. Page size is fixed at 100 when from is set. ES max_result_window caps from + size ≤ 10000 → effective ceiling from=9900. See gotcha below for deeper paging.

2. Send the request

The endpoint accepts any modern User-Agent; the SEC's fair-access policy requests (but does not enforce at this endpoint) a UA identifying your org plus a contact email. A bare Chrome UA returns 200 fine. Stay under 10 req/s aggregate to www.sec.gov + efts.sec.gov.

Through Browserbase's server-side Fetch API:

browse cloud fetch \
  "https://efts.sec.gov/LATEST/search-index?q=%22climate+risk%22&forms=10-K&dateRange=custom&startdt=2024-01-01&enddt=2024-03-31&from=0" \
  --output /tmp/edgar.json

Or any HTTP client with Accept: application/json.

3. Parse the response

{
  "took": 1975,
  "timed_out": false,
  "_shards": { "total": 50, "successful": 50, "skipped": 0, "failed": 0 },
  "hits": {
    "total": { "value": 281, "relation": "eq" },
    "max_score": 7.69,
    "hits": [ /* one entry per filing — see below */ ]
  },
  "aggregations": {
    "entity_filter":     { "buckets": [ { "key": "...", "doc_count": 2 }, ... ] },
    "sic_filter":        { "buckets": [ { "key": "6022", "doc_count": 57 }, ... ] },
    "biz_states_filter": { "buckets": [ { "key": "NY", "doc_count": 51 }, ... ] },
    "form_filter":       { "buckets": [ { "key": "10-K", "doc_count": 281 } ] }
  },
  "query": { /* the ES query echo (useful for debugging) */ }
}
  • hits.total.value is the true total. relation: "eq" means exact; "gte" appears when the bucket is capped (typically at 10,000). When you see gte, narrow your filters to get an exact count.
  • hits.hits[] is the page of matches (length ≤ 100 per request).
  • aggregations gives top-30 facet buckets for entity / sic / biz_states / form — useful for refining a too-wide query.

Each hit:

{
  "_index": "edgar_file",
  "_id": "0000815097-24-000011:ccl-20231130.htm",
  "_score": 7.69,
  "_source": {
    "adsh":            "0000815097-24-000011",
    "ciks":            ["0000815097", "0001125259"],
    "display_names":   ["CARNIVAL CORP  (CCL)  (CIK 0000815097)", "CARNIVAL PLC  (CUK, CUKPF)  (CIK 0001125259)"],
    "form":            "10-K",
    "root_forms":      ["10-K"],
    "file_type":       "10-K",
    "file_description":"10-K",
    "file_date":       "2024-01-26",
    "period_ending":   "2023-11-30",
    "biz_states":      ["FL", "X0"],
    "inc_states":      ["DE"],
    "biz_locations":   ["Miami, FL", "Southampton So15 1st, X0"],
    "sics":            ["4400", "4400"],
    "file_num":        ["001-09610", "001-15136"],
    "film_num":        ["24564723", "24564724"],
    "items":           [],
    "sequence":        1,
    "xsl":             null
  }
}

Field notes:

  • _id has the structural format {adsh}:{filename} — split on the first :. The accession number is on the left; the filename of the exhibit that matched is on the right.
  • adsh is the accession number with hyphens. Drop them to get the directory name for the URL.
  • ciks[] is always zero-padded 10-digit. Multi-CIK hits arise for joint filings (co-filers in a 10-K) and for Form 4/3/5 hits where the filer is the reporting officer and the second CIK is the issuer. The first CIK in the array is the primary filer for URL purposes.
  • display_names[] is the human-readable filer label EDGAR shows in the UI (Company (TICKER) (CIK xxx)); each entry pairs 1-to-1 with ciks[].
  • form is the exact form code (with /A amendment suffix when applicable). root_forms[] is the parent (10-K covers 10-K/A, 8-K covers 8-K/A). forms= query filter matches against root_forms[].
  • file_dateperiod_ending. Filing date is when EDGAR accepted the filing; period of report is the as-of date (e.g. fiscal year-end for a 10-K). For 8-Ks, period_ending is the event date.
  • biz_states[] / inc_states[] use 2-letter US state codes plus EDGAR's foreign codes: X0=England, X1=… (one of the international codes), A0/D0=…, XX/ZZ=other. Treat any code that's not in the US 50+DC+territories list as "foreign / unknown" for downstream consumers.
  • sics[] is the 4-digit SIC code per filer CIK. Multi-filer hits have one SIC entry per CIK.
  • items[] is populated only for 8-Ks — the list of 8-K event item codes ("2.02", "5.02", etc.). Empty for other forms.
  • _score is the relevance score from the underlying OpenSearch query. Default sort is _score desc.

4. Build the canonical filing-index URL and the direct document URL

EDGAR's filing archive uses a deterministic directory layout under https://www.sec.gov/Archives/edgar/data/{cik_int}/{adsh_no_dashes}/:

cik_int        = int(_source.ciks[0])           # strip leading zeros: "0000815097" → 815097
adsh_no_dashes = _source.adsh.replace("-", "")  # "0000815097-24-000011" → "000081509724000011"
filename       = _id.split(":", 1)[1]           # the part after the colon in the hit's _id

filing_index_url = f"https://www.sec.gov/Archives/edgar/data/{cik_int}/{adsh_no_dashes}/{adsh}-index.htm"
document_url     = f"https://www.sec.gov/Archives/edgar/data/{cik_int}/{adsh_no_dashes}/{filename}"

Both URLs verified live (HTTP 200) against https://www.sec.gov/Archives/edgar/data/815097/000081509724000011/0000815097-24-000011-index.htm and .../ccl-20231130.htm.

The filing-index page is small (~20 KB) and lists every exhibit in the filing. The direct document URL is the exact .htm or .txt that contained the matching phrase — typically the primary exhibit (the 10-K body, not Exhibit 21 subsidiaries unless that's where the term appeared).

If you need the filer's full filing history (not just this one hit), use the metadata-browse URL — that's a separate skill, but for completeness: https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK={cik_int}&type={form_code}&dateb=&owner=include&count=40.

5. Paginate

Append &from=100, &from=200, … to walk pages of 100 hits. Stop when you've collected hits.total.value results, or when len(hits.hits) < 100 (last page).

For result sets larger than 10,000:

  • ES rejects from + size > 10000 (verified: returns 200 with errorType: ResponseError, errorMessage: "search_phase_execution_exception: ... Result window is too large, from + size must be less than or equal to: [10000]").
  • There is no documented scroll/search_after surface on this endpoint.
  • The workaround: narrow by dateRange (or forms / locationCodes / sics) and walk the narrower buckets sequentially. With sort=asc + a tight date window per page, you can sweep an unbounded corpus.

6. Return the structured result

For each hits.hits[i], surface:

{
  "accession_number":   "_source.adsh",
  "filer_cik":          "_source.ciks[0]",
  "filer_name":         "_source.display_names[0]",
  "co_filer_ciks":      "_source.ciks[1:]",
  "co_filer_names":     "_source.display_names[1:]",
  "form":               "_source.form",
  "root_form":          "_source.root_forms[0]",
  "file_date":          "_source.file_date",
  "period_ending":      "_source.period_ending",
  "items_8k":           "_source.items",
  "filer_biz_state":    "_source.biz_states[0]",
  "filer_inc_state":    "_source.inc_states[0]",
  "filer_sic":          "_source.sics[0]",
  "filer_biz_location": "_source.biz_locations[0]",
  "matched_file":       "_id.split(':', 1)[1]",
  "score":              "_score",
  "filing_index_url":   "(derived per §4)",
  "document_url":       "(derived per §4)"
}

Plus, at the result-set level: total_results: hits.total.value, total_is_capped: hits.total.relation != 'eq', and (optionally, when the caller wants to refine) the four aggregations.* buckets verbatim.

Browser fallback

If the JSON endpoint is unreachable but www.sec.gov is:

  1. Open https://www.sec.gov/edgar/search/#/q=<URL-encoded-query>&forms=<csv>&dateRange=custom&startdt=...&enddt=... — the SPA is hash-routed (uses hasher.min.js); query parameters live after the #/, not after ?. The page loads with the form pre-populated and auto-submits.
  2. Wait for .divResultsContainer .result-section to render (the SPA injects results via jQuery after the same efts.sec.gov AJAX call you'd otherwise make directly).
  3. Each .result-section contains a <td class="filetype">{form}</td>, <td class="filed">{file_date}</td>, anchor <a class="preview-file" data-adsh="{adsh}" data-file-name="{filename}" href="...">, and a CIK column. Read data-adsh and data-file-name from the anchor and reconstruct the URLs per §4.
  4. Pagination is a server-side Next link in the SPA — clicking it triggers another AJAX call with from=. Same 10,000-cap applies; same Akamai protection applies to www.sec.gov (the SPA wrapper page itself), so a Verified + residential-proxy session is recommended for the SPA path. The efts.sec.gov API host has no Akamai/Cloudflare in front of it — a bare BB cloud-fetch from any IP returns 200 reliably.

The browser fallback offers no additional data versus the API — the SPA renders the exact same metadata fields the JSON returns. Use it only as a last resort.

Site-Specific Gotchas

  • CIKs must be 10-digit zero-padded. ciks=320193 returns HTTP 500 {"message":"Internal server error"}; ciks=0000320193 works. Always str(cik).zfill(10) before sending. Multi-CIK: ciks=0000320193,0001652044.

  • locationCodes is plural — singular locationCode is silently ignored. Confirmed: locationCode=CA returned the unfiltered 281 hits for the climate-risk Q1 2024 query; locationCodes=CA returned 31 hits all with biz_states={"CA"}. The consumer SPA's internal locationCode is rewritten to locationCodes before sending (verified in https://www.sec.gov/edgar/search/js/edgar_full_text_search.js ~line 290: if(searchParams.locationCode && searchParams.locationCode!='all') searchParams.locationCodes = searchParams.locationCode;).

  • locationType defaults to located (business state), not incorporated. A naive locationCodes=DE query returns 2 hits (filings where the filer's office is in Delaware, very rare); add locationType=incorporated to switch to the much more populous inc_states (Delaware-incorporated entities — 111 hits on the same query). When locationType=incorporated is set, the result set's inc_states distribution often includes Maryland (MD) too — likely from REITs and entities cross-tagged via subsidiary CIKs; treat the filter as "all hits where at least one CIK has inc_states containing your code", not strict equality.

  • forms=10-K matches 10-K/A too (and 8-K matches 8-K/A). The filter is on root_forms. If you specifically need to exclude amendments, post-filter on _source.form for an exact match.

  • No in-document snippets are returned. Despite the match_phrase query on a hidden doc_text field, the response does not include ES highlight blocks (verified: tried highlight=true, hl=on, snippet=true — none take effect; the underlying query has _source.exclude: ["doc_text"] and no highlight clause). The consumer SPA itself does not display snippets — it shows filing metadata and a link out. If the caller asks for "the exact text that matched", you must fetch the document URL separately and grep client-side for the query phrase. Note that 10-K bodies routinely run several MB and exceed Browserbase's 1 MB cloud fetch cap — use a streaming HTTP client or open the document in a session for the text extraction step.

  • hits.total.relation: "gte" means the count is capped at 10,000. When you see this, your query is broader than 10k. Narrow with dateRange / forms / locationCodes / sics to get an exact count.

  • Deep pagination is bounded at from + size ≤ 10,000. With the fixed 100-per-page size, that's max from=9900. Beyond that, the API returns a 200 envelope with an OpenSearch error JSON: search_phase_execution_exception: [illegal_argument_exception] Reason: Result window is too large, from + size must be less than or equal to: [10000] but was [10090]. There is no search_after or scroll API exposed. Workaround: narrow with a filter (most commonly a tighter dateRange), and sweep using sort=asc to walk forward in time inside each window.

  • sort=desc|asc only — other variants are silently ignored. sortBy=date, order=date, etc. all fall back to default relevance sort without an error. Verify your sort is taking effect by inspecting the first 2-3 file_date values in the result.

  • q= is required-ish — empty q=&ciks=... works (browses filings for a CIK), but the endpoint expects either q or some other selector. q= with no other filters returns relevance-sorted results across the full 10,000+ corpus.

  • Boolean operators must be uppercase. AND, OR, NOT. Lowercase variants are treated as plain tokens. Parentheses are supported: q=(foo+OR+bar)+AND+%22exact+phrase%22.

  • entityName is fuzzy and multi-match. entityName=Apple returns 88 hits across ~10 distinct "Apple"-named entities (Apple Inc., Apple Hospitality REIT, Apple Green Holding, …). For precision, resolve to a specific CIK once and use ciks= thereafter.

  • sics= filtering is exact on 4-digit codes. Comma-separated multi works (sics=2834,2835,2836 for biotech-adjacent). The result set's hits will only contain those SICs in _source.sics[] — verified.

  • X0 and other 2-char codes in biz_states[] / inc_states[] are EDGAR's foreign country codes, not US states. X0 is England, D0 is West Germany (legacy), A0 is Alberta, etc. The full table is on EDGAR's company-search help page; treat unknown codes as "international" rather than a state.

  • Transient 5xx (~36-byte error JSON) under load. Observed once during iter-1: a sics=2834 request returned a 36-byte {"message":"Internal server error"} body, then succeeded immediately on retry with the identical URL. Implement a retry-with-backoff of 2-3 attempts before propagating the error.

  • The API has CORS open (Access-Control-Allow-Origin: *) and no auth. A browser-extension or any cross-origin web client can call it directly.

  • No Akamai/Cloudflare on efts.sec.gov; Akamai IS present on www.sec.gov. A bare HTTP client gets efts.sec.gov JSON reliably. The consumer SPA host (www.sec.gov/edgar/search/) injects an Akamai detection script (/akam/13/{id} + bazadebezolkohpepadr variable) — under aggressive scraping this can challenge. The download URLs under www.sec.gov/Archives/edgar/data/... are not Akamai-protected and stream fine.

  • SEC fair-access policy: 10 req/s aggregate across all sec.gov subdomains. Stay under it. Identifying User-Agent: <YourOrg> <contact-email> is requested by policy but not enforced at the efts.sec.gov endpoint (a default Chrome UA returns 200).

  • _id filename can collide across different accessions in rare cases. Always carry the full _id (with the {adsh}: prefix) or the adsh field through downstream pipelines — never the filename alone — since two filings can have the same exhibit filename.

  • Index coverage starts 2001-05-04. A query with sort=asc and no date filter for "climate risk" on 10-Ks returned 2001-05-04 as the earliest hit, matching the SEC's published "full-text search since 2001" coverage statement. Older filings exist in EDGAR but are not in this index.

Expected Output

A search returning at least one hit:

{
  "query":         "\"climate risk\"",
  "forms":         ["10-K"],
  "date_range":    { "start": "2024-01-01", "end": "2024-03-31" },
  "sort":          "relevance",
  "total_results": 281,
  "total_is_capped": false,
  "returned":      100,
  "from":          0,
  "next_from":     100,
  "filings": [
    {
      "accession_number":    "0000815097-24-000011",
      "filer_cik":           "0000815097",
      "filer_name":          "CARNIVAL CORP  (CCL)  (CIK 0000815097)",
      "co_filer_ciks":       ["0001125259"],
      "co_filer_names":      ["CARNIVAL PLC  (CUK, CUKPF)  (CIK 0001125259)"],
      "form":                "10-K",
      "root_form":           "10-K",
      "file_date":           "2024-01-26",
      "period_ending":       "2023-11-30",
      "items_8k":            [],
      "filer_biz_state":     "FL",
      "filer_inc_state":     "DE",
      "filer_sic":           "4400",
      "filer_biz_location":  "Miami, FL",
      "matched_file":        "ccl-20231130.htm",
      "score":               7.69,
      "filing_index_url":    "https://www.sec.gov/Archives/edgar/data/815097/000081509724000011/0000815097-24-000011-index.htm",
      "document_url":        "https://www.sec.gov/Archives/edgar/data/815097/000081509724000011/ccl-20231130.htm",
      "matched_snippet":     null
    }
  ],
  "aggregations": {
    "top_filers":   [{ "name": "Carlyle Group Inc.  (CG, CGABL)  (CIK 0001527166)", "count": 2 }],
    "top_sics":     [{ "code": "6022", "count": 57 }, { "code": "6021", "count": 41 }],
    "top_states":   [{ "code": "NY", "count": 51 }, { "code": "CA", "count": 31 }],
    "top_forms":    [{ "code": "10-K", "count": 281 }]
  }
}

A search returning zero hits:

{
  "query": "\"material weakness\"",
  "forms": ["8-K"],
  "ciks":  ["0000320193"],
  "total_results": 0,
  "total_is_capped": false,
  "returned": 0,
  "filings": []
}

A search where the total count is capped (broaden the alternation, narrow with filters):

{
  "query": "the",
  "forms": ["10-K", "8-K"],
  "total_results": 10000,
  "total_is_capped": true,
  "returned": 100,
  "from": 0,
  "next_from": 100,
  "filings": [ /* first 100 hits */ ],
  "note": "Result set exceeds 10,000. Narrow with dateRange / locationCodes / sics and re-query to get an exact count."
}

A search where the requested page is past the ES window:

{
  "query": "the",
  "from":  10000,
  "error": "result_window_exceeded",
  "message": "from + size must be less than or equal to 10000. Narrow filters and re-paginate within the narrower set."
}

A search where the CIK was passed un-padded (the input must be fixed before retrying):

{
  "error":   "invalid_cik",
  "message": "ciks must be 10-digit zero-padded; pad with leading zeros and retry. Received: '320193' → should be '0000320193'."
}
how to use search-edgar-fulltext

How to use search-edgar-fulltext on Cursor

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1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add search-edgar-fulltext
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$browse install sec.gov/search-edgar-fulltext-dpk6r2

The skills CLI fetches search-edgar-fulltext from GitHub repository sec.gov/search-edgar-fulltext-dpk6r2 and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
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│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/search-edgar-fulltext

Reload or restart Cursor to activate search-edgar-fulltext. Access the skill through slash commands (e.g., /search-edgar-fulltext) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Implementation Guide

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Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.828 reviews
  • Ganesh Mohane· Dec 28, 2024

    I recommend search-edgar-fulltext for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Charlotte Mehta· Dec 28, 2024

    Useful defaults in search-edgar-fulltext — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Diya Perez· Dec 24, 2024

    search-edgar-fulltext is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Shikha Mishra· Dec 4, 2024

    search-edgar-fulltext has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Omar Chen· Nov 27, 2024

    search-edgar-fulltext has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Sakshi Patil· Nov 19, 2024

    Useful defaults in search-edgar-fulltext — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Aditi Thompson· Nov 19, 2024

    I recommend search-edgar-fulltext for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Min Diallo· Nov 15, 2024

    search-edgar-fulltext reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Henry Diallo· Oct 18, 2024

    Keeps context tight: search-edgar-fulltext is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Chaitanya Patil· Oct 10, 2024

    search-edgar-fulltext is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

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