financial-report-analyzer-proEN: Extract, normalize and analyze key metrics from corporate financial reports (10-K, 10-Q, A-share annual/interim reports, IFRS/GAAP/CAS PDFs). Produces si...
Install via ClawdBot CLI:
clawdbot install boboy-j/financial-report-analyzer-proGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
https://github.com/openclaw-skills/financial-report-analyzerAudited May 27, 2026 · audit v1.0
Generated Sep 29, 2026
An individual investor uploads a 10-K or A-share annual report PDF and asks the skill to extract key financials, compute ROE, gross margin, and cash conversion cycle, and flag earnings-management signals before deciding whether to dig deeper. The skill returns a traceable 5-section report with page-level provenance so the user can verify every number.
A buy-side analyst uses the skill to normalize 10-K and A-share annual reports across 3-5 comparable companies into a common chart of accounts, then generates side-by-side YoY ratios and peer percentile rankings. The built-in peer DB or a custom Parquet benchmark lets them quickly identify outliers in margin and leverage.
A PE/VC investment associate feeds a Chinese or US IPO prospectus into the skill to surface red flags such as related-party transaction anomalies, goodwill concentration, and abnormal receivables growth relative to revenue. The skill produces a compliance audit log so the finding can be attached to the investment memo.
A commercial bank credit officer periodically runs the skill over listed borrower filings to track debt ratio, interest coverage, Z-score, and OCF/NI trends across quarters. Alert thresholds from the 18 red-flag heuristics trigger follow-up credit reviews before covenant breaches.
An accounting or finance student uploads a real annual report and asks the skill to explain the 40+ ratios, Dupont decomposition, and three-statement linkages with source citations. The structured JSON output and Markdown rendering make it easy to cross-check textbook formulas against actual disclosures.
The core analyzer is freely distributed via the openclaw-skill registry, but advanced peer benchmarking requires a curated industry median database. A paid tier provides quarterly refreshed peer benchmarks covering major global exchanges.
Expose the pipeline (ingest → normalize → compute → red-flag → render) as a metered REST API so robo-advisors, brokerage apps, and IR platforms can embed financial report analysis directly into their products. Pricing is per-report or per-seat.
Deploy the skill inside investment banks, audit firms, and corporate finance departments as an on-prem or VPC-hosted tool integrated with document management systems. Includes audit log retention, custom chart-of-accounts mapping, and regulator-specific red-flag rulesets.
💬 Integration Tip
Set FINREPORT_PEER_DB to a Parquet/CSV of industry medians to unlock percentile rankings, and call scripts/run_pipeline.py then render_report.py with --format md for human outputs or --format json to feed downstream dashboards. For web channels, pair with web-prism-artifact to auto-render the structured artifact inline.
Scored Jun 5, 2026
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