# tasktime

> Use this tool when you need to track and visualize the time spent on tasks to benchmark learning progression. It solves problems of manual time tracking and provides insights into task duration, with inputs of task names and durations, and outputs of auto-saved logs and visualizations. Ideal for use in iterative learning processes where efficiency and progress monitoring are crucial.

Canonical page: https://skillsregistry.net/skills/g9pedro-tasktime  
JSON: https://api.skillsregistry.net/v1/skills/g9pedro-tasktime

## Description

CLI task timer for AI agents — benchmark learning progression with auto-save logs and visualizations.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-08-23

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** ai-ml
- **Updated:** 2026-08-23

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/g9pedro-tasktime)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "g9pedro-tasktime"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/g9pedro-tasktime` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/g9pedro-tasktime/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt