# Agendum

> Use this tool when you need to manage and track tasks, decisions, and work packages across multiple sessions, enabling cross-session continuity and scoped memory for AI agents. It solves problems of task fragmentation, decision loss, and context switching, providing a unified interface for inputting tasks and outputting tracked progress. Ideal for use cases requiring persistent memory and task management, such as complex workflows and multi-step decision-making processes.

Canonical page: https://skillsregistry.net/skills/io-github-sralli-agendum  
JSON: https://api.skillsregistry.net/v1/skills/io-github-sralli-agendum

## Description

AI agent memory: task tracking, scoped work packages, decisions, and cross-session continuity

## Trust

- **Trust score (0–1):** 0.84
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 0.3.4
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/io.github.sralli%2Fagendum)
- **Repository:** <https://github.com/sralli/agendum>

## 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": "io-github-sralli-agendum"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/io-github-sralli-agendum` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/io-github-sralli-agendum/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