time-tracking-4-rescuetime-data-retrieval

Sub-skill of time-tracking: 4. RescueTime - Data Retrieval.

5 stars

Best use case

time-tracking-4-rescuetime-data-retrieval is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Sub-skill of time-tracking: 4. RescueTime - Data Retrieval.

Teams using time-tracking-4-rescuetime-data-retrieval 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/4-rescuetime-data-retrieval/SKILL.md --create-dirs "https://raw.githubusercontent.com/vamseeachanta/workspace-hub/main/.agents/skills/_archive/business/productivity/time-tracking/4-rescuetime-data-retrieval/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/4-rescuetime-data-retrieval/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How time-tracking-4-rescuetime-data-retrieval Compares

Feature / Agenttime-tracking-4-rescuetime-data-retrievalStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Sub-skill of time-tracking: 4. RescueTime - Data Retrieval.

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

# 4. RescueTime - Data Retrieval

## 4. RescueTime - Data Retrieval


**REST API - Analytics:**
```bash
# Get summary data
curl -s "https://www.rescuetime.com/anapi/data" \
    -d "key=$RESCUETIME_API_KEY" \
    -d "format=json" \
    -d "perspective=rank" \
    -d "resolution_time=day" \
    -d "restrict_kind=overview" | jq

# Get data for specific date range
curl -s "https://www.rescuetime.com/anapi/data" \
    -d "key=$RESCUETIME_API_KEY" \
    -d "format=json" \
    -d "restrict_begin=2025-01-01" \
    -d "restrict_end=2025-01-31" \
    -d "restrict_kind=overview" | jq

# Get activity data by category
curl -s "https://www.rescuetime.com/anapi/data" \
    -d "key=$RESCUETIME_API_KEY" \
    -d "format=json" \
    -d "restrict_kind=category" \
    -d "resolution_time=week" | jq

# Get productivity data
curl -s "https://www.rescuetime.com/anapi/data" \
    -d "key=$RESCUETIME_API_KEY" \
    -d "format=json" \
    -d "restrict_kind=productivity" | jq

# Get activity details
curl -s "https://www.rescuetime.com/anapi/data" \
    -d "key=$RESCUETIME_API_KEY" \
    -d "format=json" \
    -d "restrict_kind=activity" \
    -d "resolution_time=day" | jq

# Get efficiency data (requires Premium)
curl -s "https://www.rescuetime.com/anapi/data" \
    -d "key=$RESCUETIME_API_KEY" \
    -d "format=json" \
    -d "restrict_kind=efficiency" | jq
```

**Python - RescueTime Client:**
```python
import requests
from datetime import datetime, timedelta
import os

class RescueTimeClient:
    """RescueTime API client."""

    BASE_URL = "https://www.rescuetime.com/anapi"

    def __init__(self, api_key=None):
        self.api_key = api_key or os.environ.get("RESCUETIME_API_KEY")

    def _request(self, endpoint, params=None):
        """Make API request."""
        params = params or {}
        params["key"] = self.api_key
        params["format"] = "json"

        response = requests.get(
            f"{self.BASE_URL}/{endpoint}",
            params=params
        )
        response.raise_for_status()
        return response.json()

    def get_daily_summary(self, date=None):
        """Get daily summary data."""
        params = {
            "perspective": "rank",
            "resolution_time": "day",
            "restrict_kind": "overview"
        }

        if date:
            params["restrict_begin"] = date.strftime("%Y-%m-%d")
            params["restrict_end"] = date.strftime("%Y-%m-%d")

        return self._request("data", params)

    def get_date_range_data(
        self,
        start_date,
        end_date,
        restrict_kind="overview",
        resolution="day"
    ):
        """Get data for date range."""
        params = {
            "restrict_begin": start_date.strftime("%Y-%m-%d"),
            "restrict_end": end_date.strftime("%Y-%m-%d"),
            "restrict_kind": restrict_kind,
            "resolution_time": resolution
        }

        return self._request("data", params)

    def get_productivity_data(self, start_date=None, end_date=None):
        """Get productivity scores."""
        params = {"restrict_kind": "productivity"}

        if start_date:
            params["restrict_begin"] = start_date.strftime("%Y-%m-%d")
        if end_date:
            params["restrict_end"] = end_date.strftime("%Y-%m-%d")

        return self._request("data", params)

    def get_category_data(
        self,
        start_date=None,
        end_date=None,
        resolution="day"
    ):
        """Get data grouped by category."""
        params = {
            "restrict_kind": "category",
            "resolution_time": resolution
        }

        if start_date:
            params["restrict_begin"] = start_date.strftime("%Y-%m-%d")
        if end_date:
            params["restrict_end"] = end_date.strftime("%Y-%m-%d")

        return self._request("data", params)

    def get_activity_data(
        self,
        start_date=None,
        end_date=None,
        resolution="day"
    ):
        """Get detailed activity data."""
        params = {
            "restrict_kind": "activity",
            "resolution_time": resolution
        }

        if start_date:
            params["restrict_begin"] = start_date.strftime("%Y-%m-%d")
        if end_date:
            params["restrict_end"] = end_date.strftime("%Y-%m-%d")

        return self._request("data", params)

    def get_focus_time(self, start_date=None, end_date=None):
        """Calculate focus time from activities."""
        productivity = self.get_productivity_data(start_date, end_date)

        focus_time = 0
        total_time = 0

        for row in productivity.get("rows", []):
            # row format: [rank, time_seconds, productivity]
            time_seconds = row[1]
            productivity_score = row[2]  # -2 to 2

            total_time += time_seconds
            if productivity_score >= 1:  # Productive or very productive
                focus_time += time_seconds

        return {
            "focus_time_seconds": focus_time,
            "focus_time_hours": focus_time / 3600,
            "total_time_seconds": total_time,
            "total_time_hours": total_time / 3600,
            "focus_percentage": (focus_time / total_time * 100) if total_time > 0 else 0
        }


# Example usage
if __name__ == "__main__":
    client = RescueTimeClient()

    # Get today's summary
    today = client.get_daily_summary()
    print("Today's Activity:")

*Content truncated — see parent skill for full reference.*

Related Skills

data-validation-reporter

5
from vamseeachanta/workspace-hub

Generate interactive validation reports with quality scoring, missing data analysis, and type checking. Combines Pandas validation, Plotly visualization, and YAML configuration for comprehensive data quality reporting.

worldenergydata-source-readiness

5
from vamseeachanta/workspace-hub

Route agents to the canonical worldenergydata source-readiness skill and summary script. Use when asked for worldenergydata data completeness, data locations, latest known data dates, scheduler freshness, source-readiness status, or acceptance-criteria inputs across the repo ecosystem.

sodir-data-extractor

5
from vamseeachanta/workspace-hub

Extract and process Norwegian Petroleum Directorate field and production data from SODIR

metocean-data-fetcher

5
from vamseeachanta/workspace-hub

Fetch real-time and historical metocean data from NDBC, CO-OPS, Open-Meteo, ERDDAP, and MET Norway. Use for buoy data retrieval, tidal observations, marine forecasts, and multi-source data fusion.

energy-data-visualizer

5
from vamseeachanta/workspace-hub

Interactive visualization for oil and gas production data analysis using Plotly dashboards

bsee-data-extractor

5
from vamseeachanta/workspace-hub

Extract and process BSEE (Bureau of Safety and Environmental Enforcement) data including production, WAR (Well Activity Reports), and APD (Application for Permit to Drill) data. Use for querying production data, well activities, drilling permits, completions, and workovers by API number, block, lease, or field with automatic data normalization and caching.

tax-return-data-capture-and-archival

5
from vamseeachanta/workspace-hub

Capture structured tax return summaries as YAML for year-over-year comparison, with fallback to manual PDF download and relocation when automation fails

tax-filing-session-setup-with-github-tracking

5
from vamseeachanta/workspace-hub

Structured workflow for preparing and tracking a tax filing session using prepared documents, task checklist, and GitHub issue cross-referencing

repo-separation-for-sensitive-data

5
from vamseeachanta/workspace-hub

Architecture pattern for splitting confidential data and reusable algorithms across repos

metadata-only-wiki-sweep-workflow

5
from vamseeachanta/workspace-hub

Disciplined inventory process for cataloging documents by filename/path without content claims, using parent-centric grouping to prevent stub proliferation

metadata-only-inventory-sweep

5
from vamseeachanta/workspace-hub

Execute constrained file inventory sweeps with metadata-only stubs and validation, useful for staged documentation work on large file sets

handle-freetaxusa-session-timeouts

5
from vamseeachanta/workspace-hub

Recover from FreeTaxUSA session timeout dialogs blocking form submission and navigation