Skill: bytesagain3/terminal-dashboard (version 1.0.0)

--- version: "1.0.0" name: Sampler description: "Tool for shell commands execution, visualization and alerting. Configured with a simple YAML file. terminal-dashboard, go, alerting, charts, cmd." --- # Terminal Dashboard Terminal Dashboard v2.0.0 — a data toolkit for building data pipelines and tracking data operations from the command line. Ingest, transform, query, filter, aggregate, and visualize your data — all logged locally with timestamps for full traceability. ## Why Terminal Dashboard? - Works entirely offline — your data never leaves your machine - Simple command-line interface, no GUI needed - Timestamped logging for every operation - Export to JSON, CSV, or plain text anytime - Automatic history and activity tracking - Searchable records across all data pipeline stages ## Getting Started ```bash # See all available commands terminal-dashboard help # Check current health status terminal-dashboard status # View summary statistics terminal-dashboard stats ``` ## Commands ### Data Pipeline Commands Each command works in two modes: run without arguments to view recent entries, or pass input to record a new entry. | Command | Description | |---------|-------------| | `terminal-dashboard ingest <input>` | Record data ingestion events (file imports, API pulls, stream captures) | | `terminal-dashboard transform <input>` | Log data transformations (format conversions, cleaning steps, enrichments) | | `terminal-dashboard query <input>` | Record queries executed (SQL, API calls, search operations) | | `terminal-dashboard filter <input>` | Log filter operations (row filtering, column selection, deduplication) | | `terminal-dashboard aggregate <input>` | Record aggregation operations (group-by, rollups, summaries) | | `terminal-dashboard visualize <input>` | Log visualization outputs (charts generated, dashboards updated) | | `terminal-dashboard export <input>` | Record export operations (file writes, API pushes, report generation) | | `terminal-dashboard sample <input>` | Log sampling operations (random samples, stratified picks, head/tail) | | `terminal-dashboard schema <input>` | Record schema operations (schema detection, validation rules, migrations) | | `terminal-dashboard validate <input>` | Log validation results (data quality checks, constraint tests, anomalies) | | `terminal-dashboard pipeline <input>` | Record pipeline operations (end-to-end runs, DAG executions, orchestration) | | `terminal-dashboard profile <input>` | Log profiling results (data profiling, column stats, distribution analysis) | ### Utility Commands | Command | Description | |---------|-------------| | `terminal-dashboard stats` | Show summary statistics across all log categories | | `terminal-dashboard export <fmt>` | Export all data (formats: `json`, `csv`, `txt`) | | `terminal-dashboard search <term>` | Search across all entries for a keyword | | `terminal-dashboard recent` | Show the 20 most recent history entries | | `terminal-dashboard status` | Health check — version, data dir, entry count, disk usage | | `terminal-dashboard help` | Show the built-in help message | | `terminal-dashboard version` | Print version (v2.0.0) | ## Data Storage All data is stored locally in `~/.local/share/terminal-dashboard/`. Structure: - **`ingest.log`**, **`transform.log`**, **`query.log`**, etc. — one log file per command, pipe-delimited (`timestamp|value`) - **`history.log`** — unified activity log across all commands - **`export.json`** / **`export.csv`** / **`export.txt`** — generated export files Each entry is stored as `YYYY-MM-DD HH:MM|<input>`. Use `export` to back up your data anytime. ## Requirements - Bash 4+ (uses `set -euo pipefail`) - Standard Unix utilities (`date`, `wc`, `du`, `tail`, `grep`, `sed`, `cat`) - No external dependencies or internet access needed ## When to Use 1. **Data pipeline logging** — Track every step of your ETL/ELT pipeline from ingestion through transformation to export, creating a complete audit trail 2. **Data quality monitoring** — Use `validate` and `profile` to record data quality checks and catch anomalies before they reach production 3. **Schema change tracking** — Log schema migrations and validation rules so you always know what changed and when 4. **Ad-hoc analysis journaling** — Record queries, filters, and aggregations during exploratory analysis so you can reproduce your findings later 5. **Pipeline debugging** — When a data pipeline breaks, search through ingest, transform, and export logs to pinpoint where things went wrong ## Examples ```bash # Record a data ingestion event terminal-dashboard ingest "Loaded 2.4M rows from sales_2024.csv into staging" # Log a transformation step terminal-dashboard transform "Normalized phone numbers, deduplicated by email — 12k dupes removed" # Record a query terminal-dashboard query "SELECT region, SUM(revenue) FROM sales GROUP BY region — 8 rows returned" # Log a validation check terminal-dashboard validate "Schema check passed: all 47 columns match expected types" # Record a pipeline run terminal-dashboard pipeline "Daily ETL completed: ingest→clean→aggregate→export in 4m 23s" # Export everything to JSON terminal-dashboard export json # Search logs for a dataset terminal-dashboard search "sales_2024" ``` ## Output All commands output to stdout. Redirect to a file if needed: ```bash terminal-dashboard stats > pipeline-report.txt terminal-dashboard export csv ``` ## Configuration Set `TERMINAL_DASHBOARD_DIR` environment variable to override the default data directory (`~/.local/share/terminal-dashboard/`). --- Powered by BytesAgain | bytesagain.com | [REDACTED_SECRET]


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)