Finance tasks
Clean data xlsExcel financial modeling
Indexedanthropics/financial-services
Clean Spreadsheet DataFinance Skill
A financial analysis workflow for cleaning messy Excel spreadsheet data. It covers whitespace trimming, casing normalization, number-as-text conversion, date standardization, deduplication, encoding repair, and error flagging. Prefers transparent helper-column formulas over hardcoded values and requires user confirmation for destructive operations.
- Snapshot quality
- 80/100
- Snapshot risk
- Medium
- Audit conclusion
- Needs review
Discovery
What this Skill helps an agent do.
Search metadata is limited to this summary, the controlled finance taxonomy, and relation labels. Detailed upstream instructions are not part of the Search Index.
Domains and assets
Fundamental analysisPublic equities
Search aliases and tags
clean this dataclean up this sheetnormalize this datafix formattingdedupestandardize this columnclean-data-xlsdata-cleaningspreadsheet-prepnormalizationdeduplicationfinancial-analysis
Trust
Evidence from the captured directory.
This content snapshot assessment does not certify the repository, current files, or installation environment. "Not verified" means the captured files did not support a Yes or No conclusion.
License
Apache-2.0Yes
GitHub reports the repository license as Apache License 2.0.
Review state
- Automated review
- Automated review
- Install tested
- No
- Human reviewed
- Not verified
Snapshot
- Files reviewed
- 1
- Captured
- 2026-07-29 07:31 UTC
- Snapshot ID
- fsh-clean-data-xls-2026-07-29-001
Permissions
FilesystemRead
YesThe workflow reads spreadsheet data to profile columns, detect issues, and inspect cell values.
FilesystemWrite
YesThe workflow writes helper-column formulas and may overwrite in-place with computed values when explicitly requested.
NetworkAccess
NoNo network access or web search is required by the workflow.
ShellExecution
NoNo shell commands or scripts are included or referenced in the captured directory.
CodeExecution
NoThe workflow references Python/openpyxl for standalone .xlsx files and Office JS for Excel add-in environments, but no code files are included in the captured directory.
ExternalCredentials
NoNo external credentials or paid data sources are required for spreadsheet data cleaning.
Dependencies
openpyxl
Python library for standalone .xlsx file processing
Python openpyxl library for reading and writing .xlsx files outside Excel.
Data sources named by the Skill
User-provided spreadsheet
The user provides the spreadsheet data to be cleaned.
Snapshot assessment
80/100
Pineify Finance Skill snapshot assessment, version 1.0.0. Generated 2026-07-29 07:31 UTC.
Medium risk · Needs review
Skill structure
80/100Instruction clarity
100/100Dependency transparency
65/100Permission transparency
75/100Safety guardrails
65/100Finance task fit
100/100Audit findings
Medium
Dependency manifest is absent from the snapshot
No requirements.txt or equivalent manifest is included in the captured directory, though openpyxl is referenced in the instructions.
Low
No financial advice boundary
The workflow prepares data for financial analysis but includes no explicit investment advice disclaimer.
Sources and relations
Context around this Skill.
Repository
anthropics/financial-services
topic
Clean spreadsheet data
P0 relation label. No public page yet.
agent
Claude Code
P0 relation label. No public page yet.
collection
Financial analysis
P0 relation label. No public page yet.
guide
Reviewing finance skills before install
P0 relation label. No public page yet.
Registry
Read this record as data.
The public record includes the page-safe snapshot, evidence, assessment, taxonomy, and relations. Internal revision fields stay outside the public projection.
- Record ID
- github:anthropics/financial-services:plugins/vertical-plugins/financial-analysis/skills/clean-data-xls
- Snapshot ID
- fsh-clean-data-xls-2026-07-29-001
This page is an informational registry entry, not investment advice or a security guarantee. A high content quality score does not make the Skill safe for every environment. Review current files, permissions, data sources, and financial assumptions before use.