A vendor-neutral skill for working with Inline XBRL (iXBRL) and the underlying XBRL stack — covering the major regulators (SEC EDGAR, ESMA ESEF, UK FRC / Companies House / HMRC, Dutch SBR / KvK / AFM, EBA, EIOPA), the IFRS Accounting Taxonomy, FASB US-GAAP, and the Arelle validation toolchain.
Built for the people who actually file: accountants, auditors, controllers, investor-relations teams, banking and insurance supervisory-reporting analysts, and the engineers who write the code that produces their iXBRL.
SKILL.md— first principles, regulator routing, and the validation pipeline. Loaded automatically when the skill triggers.references/— load on demand:spec.md— Inline XBRL 1.1, XBRL 2.1, XDT (Dimensions), Transformation Registry 4, calculation linkbase semantics.taxonomies.md— IFRS, ESEF, US-GAAP / DEI / SRT, UK FRC Suite, Dutch NT / SBR, EBA & EIOPA DPM, plus EDINET / CNMV / SBR-AU / MCA.esef.md— ESEF legal basis, Reporting Manual rules, anchoring, block tagging, report package, NCAs, andESEF.*error codes.sec-edgar.md— SEC iXBRL phase-in, EDGAR Filer Manual sections, DEI cover-page tagging,EFM.6.05.*codes, recent rules (Pay-Versus-Performance, cybersecurity disclosure, tailored shareholder reports).validation.md— Arelle CLI, plugins, formula linkbase, Calc 1.1, a master list ofESEF.*/EFM.*/xbrl.*/xbrldie:*error codes with root cause and fix, and 25 anti-patterns that pass syntax but fail review.
scripts/validate_with_arelle.sh— wrapsarelleCmdLinewith the right plugin chain per profile (esef,efm,ukfrc,hmrc,core).scripts/check_facts.py— pure-Python pre-flight that catches cheap-to-detect issues (missingdecimals, dangling continuation chains, undefined contexts/units, non-ISO currency measures,decimals="INF"abuse, inconsistent duplicate facts) before you spend cycles in Arelle.
Every factual claim in this skill is tied to a primary source from the
issuer or standard-setter (xbrl.org, ifrs.org, esma.europa.eu, sec.gov,
fasb.org, frc.org.uk, sbr-nl.nl, eba.europa.eu, eiopa.europa.eu, the
Arelle GitHub repository). Each references/*.md ends with a
Sources list of the URLs consulted. Versions and rule numbers were
verified at the time of writing — re-check the publisher's page before
relying on a specific version for a regulated filing.
This is an AI-agent skill — a self-contained directory of markdown and scripts that any agent harness supporting the skill convention can load.
Drop the directory under your agent's skills root. Common locations
include ~/.<agent>/skills/ixbrl/ or a project-local
.agents/skills/ixbrl/. Most harnesses auto-discover the skill from
the name and description in the SKILL.md frontmatter.
SKILL.md lives at the root of this public repo, so any runtime with
the skills CLI can install it directly:
npx skills add MaxSchoon/ixbrlskills.sh has no separate submission step — its directory is populated
from CLI install telemetry. The skill becomes discoverable (via
npx skills find ixbrl) and climbs the listing as people install it
with the command above.
The skill is harness-agnostic. It works with any AI-agent runtime that:
- Loads skills from a directory of markdown files with YAML
frontmatter (
name,description). - Routes user requests to relevant skills based on the description.
- Lets the agent read additional reference files on demand.
That includes terminal-based coding agents, IDE-integrated agents, chat-based agents, and SDK-built custom agents. The skill makes no assumptions about which model or vendor you use — only about the skill-loading convention.
The bundled scripts require Python 3.10+, lxml, and (for full
validation) pip install arelle-release. The skill is useful even
without those dependencies — the references work on their own.
MIT — see LICENSE. Third-party attribution notices are in
NOTICE.
This skill is not legal, accounting, audit, or filing advice. iXBRL filings carry regulatory consequence; always verify against the live publisher source before relying on a specific rule for a regulated filing. The skill lowers the cost of getting to the right page of the right manual; it does not replace professional judgement.
Issues and pull requests welcome. Two principles:
- Source discipline. Every new factual claim must cite a primary authoritative URL the contributor has actually fetched.
- Generality. This is a public, vendor-neutral skill. No product-specific naming, no internal jargon, no jurisdiction-narrow shortcuts presented as universal.