anonymise

Anonymise CSV files by removing personal identifying information and adding datetime stamps. Use when user wants to process a new CSV file or strip PII from data.

16 stars

Best use case

anonymise is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Anonymise CSV files by removing personal identifying information and adding datetime stamps. Use when user wants to process a new CSV file or strip PII from data.

Teams using anonymise should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/anonymise/SKILL.md --create-dirs "https://raw.githubusercontent.com/diegosouzapw/awesome-omni-skill/main/skills/backend/anonymise/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/anonymise/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How anonymise Compares

Feature / AgentanonymiseStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Anonymise CSV files by removing personal identifying information and adding datetime stamps. Use when user wants to process a new CSV file or strip PII from data.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# CSV Anonymiser

When the user wants to anonymise a CSV file or process new data:

## 1. Check .gitignore

First, verify that CSV files are excluded from git:

```bash
cat .gitignore
```

If `*.csv` is not present, add it:

```bash
echo "*.csv" >> .gitignore
```

## 2. Identify the CSV File

The script can auto-detect new CSV files:
- **Auto-detection**: Files without a timestamp pattern (YYYYMMDD_HHMMSS) in their name
- **New files**: Any CSV file that hasn't been processed yet
- If multiple new files exist, the script will list them and ask user to specify which one

## 3. Remove Personal Identifying Information

Columns to remove are configured in `~/.agents/skills/anonymise/config.txt`:
- One column header per line
- Lines starting with `#` are comments
- Default includes `"Record - Airtable ID"` (PII)

Process the file:
1. Read the CSV file
2. Remove all columns listed in `~/.agents/skills/anonymise/config.txt`
3. Keep all other columns intact
4. Preserve the header row (minus the removed columns)

## 4. Add Datetime Stamp

The script will:
1. Create a new file with format: `YYYYMMDD_HHMMSS.csv` (just the timestamp)
2. Delete the original file

Example: `ILR data 25_26-Social value data for Dingley.csv` becomes `20231216_143022.csv`

## 5. Run the Anonymisation Script

Execute the Python script located in the same directory as this skill:

**Auto-detect mode** (finds CSV files without timestamps):
```bash
python3 ~/.agents/skills/anonymise/anonymise.py
```

**Specific file mode**:
```bash
python3 ~/.agents/skills/anonymise/anonymise.py "filename.csv"
```

If multiple new files are found in auto-detect mode, the script will list them and you'll need to specify which one to process.

## 6. Confirm Completion

After processing:
1. Confirm the anonymised file was created with timestamp
2. Confirm the original file was removed
3. Confirm .gitignore includes `*.csv`
4. Remind user that CSV files won't be committed to git

## Notes

- Uses British English spelling throughout
- Handles UTF-8 BOM encoding (`utf-8-sig`) for compatibility
- Preserves all data except the first column
- Assumes consistent CSV structure across files
- Files are automatically excluded from version control

Related Skills

bgo

10
from diegosouzapw/awesome-omni-skill

Automates the complete Blender build-go workflow, from building and packaging your extension/add-on to removing old versions, installing, enabling, and launching Blender for quick testing and iteration.

Coding & Development

obsidian-daily

16
from diegosouzapw/awesome-omni-skill

Manage Obsidian Daily Notes via obsidian-cli. Create and open daily notes, append entries (journals, logs, tasks, links), read past notes by date, and search vault content. Handles relative dates like "yesterday", "last Friday", "3 days ago".

obsidian-additions

16
from diegosouzapw/awesome-omni-skill

Create supplementary materials attached to existing notes: experiments, meetings, reports, logs, conspectuses, practice sessions, annotations, AI outputs, links collections. Two-step process: (1) create aggregator space, (2) create concrete addition in base/additions/. INVOKE when user wants to attach any supplementary material to an existing note. Triggers: "addition", "create addition", "experiment", "meeting notes", "report", "conspectus", "log", "practice", "annotations", "links", "link collection", "аддишн", "конспект", "встреча", "отчёт", "эксперимент", "практика", "аннотации", "ссылки", "добавь к заметке".

observe

16
from diegosouzapw/awesome-omni-skill

Query and manage Observe using the Observe CLI. Use when the user wants to run OPAL queries, list datasets, manage objects, or interact with their Observe tenant from the command line.

observability-review

16
from diegosouzapw/awesome-omni-skill

AI agent that analyzes operational signals (metrics, logs, traces, alerts, SLO/SLI reports) from observability platforms (Prometheus, Datadog, New Relic, CloudWatch, Grafana, Elastic) and produces practical, risk-aware triage and recommendations. Use when reviewing system health, investigating performance issues, analyzing monitoring data, evaluating service reliability, or providing SRE analysis of operational metrics. Distinguishes between critical issues requiring action, items needing investigation, and informational observations requiring no action.

nvidia-nim

16
from diegosouzapw/awesome-omni-skill

NVIDIA NIM inference microservices for deploying AI models with OpenAI-compatible APIs, self-hosted or cloud

numpy-string-ops

16
from diegosouzapw/awesome-omni-skill

Vectorized string manipulation using the char module and modern string alternatives, including cleaning and search operations. Triggers: string operations, numpy.char, text cleaning, substring search.

nova-act-usability

16
from diegosouzapw/awesome-omni-skill

AI-orchestrated usability testing using Amazon Nova Act. The agent generates personas, runs tests to collect raw data, interprets responses to determine goal achievement, and generates HTML reports. Tests real user workflows (booking, checkout, posting) with safety guardrails. Use when asked to "test website usability", "run usability test", "generate usability report", "evaluate user experience", "test checkout flow", "test booking process", or "analyze website UX".

notebook-writer

16
from diegosouzapw/awesome-omni-skill

Create and document Jupyter notebooks for reproducible analyses

nomistakes

16
from diegosouzapw/awesome-omni-skill

Error prevention and best practices enforcement for agent-assisted coding. Use when writing code to catch common mistakes, enforce patterns, prevent bugs, validate inputs, handle errors, follow coding standards, avoid anti-patterns, and ensure code quality through proactive checks and guardrails.

nlss

16
from diegosouzapw/awesome-omni-skill

Workspace-first R statistics suite with subskills and agent-run metaskills (including run-demo for guided onboarding, explain-statistics for concept explanations, explain-results for interpreting outputs, format-document for NLSS format alignment, screen-data for diagnostics, check-assumptions for model-specific checks, and write-full-report for end-to-end reporting) that produce NLSS format tables/narratives and JSONL logs from CSV/SAV/RDS/RData/Parquet. Covers descriptives, frequencies/crosstabs, correlations, t-tests/ANOVA/nonparametric, regression/mixed models, SEM/CFA/mediation, EFA, power, reliability/scale analysis, assumptions, plots, missingness/imputation, data transforms, and workspace management.

nexus-bootstrap

16
from diegosouzapw/awesome-omni-skill

Enables your AI agent to discover and install skills from the Nexus Skills Marketplace. Install this skill first to unlock self-service skill management.