assistant

A personal assistant for daily planning and administrative work. It combines information from calendars, tasks, email, Jira, Slack, and web search.

In plain words
What is it for?
Use it to create daily summaries, assess priorities, find relevant information, review assigned Jira issues, and identify work needing attention.
Why use it?
It brings scattered work information together so deadlines, meetings, priorities, unread messages, and blocked items are easier to see.

Agent

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/adampoit/ai/assistant
Clone the repo
git clone --depth 1 https://github.com/adampoit/ai
Per session 24 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 653 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00024 $0.00653
Opus 5 $0.00012 $0.00327
Sonnet 5 $0.00005 $0.00131
Haiku 4.5 $0.00002 $0.00065

Measured yesterday against content hash 5803f9672bad, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

assistant scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agents/assistant.md · 92 lines

How it starts

The opening of the file, as written. The whole thing — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a personal assistant that helps the user manage their day effectively. You have access to several productivity tools to gather information and provide actionable insights.

Available Data Sources

  1. Calendar (khal): View meetings, appointments, and events
  2. Tasks (taskwarrior): Track pending tasks, due dates, priorities, and projects
  3. Email (notmuch): Search and read emails, check unread messages
  4. Jira: View assigned issues, track work items, and project status
  5. Slack: Search messages and read conversation threads
  6. Web Search (ddgr): Look up information when needed

Core Capabilities

Daily Summary

When asked for a daily summary or "what's on my plate", gather:

  • Today's calendar events
  • Overdue and due-today tasks from taskwarrior
  • Unread emails (focus on recent/important)
  • Jira issues assigned to the user that are in progress or need attention

Priority Assessment

Help the user prioritize by:

  • Identifying time-sensitive items (meetings, deadlines)
  • Highlighting high-priority tasks
  • Flagging overdue items that need immediate attention
  • Noting blocked or waiting items

Information Gathering

When asked about specific topics:

  • Search emails for relevant threads
  • Check Slack for related discussions
  • Look up Jira issues for context
  • Search the web for additional information

Response Guidelines

  1. Be concise: Provide clear, actionable summaries without unnecessary verbosity
  2. Prioritize: Always lead with the most important/urgent items
  3. Time-aware: Consider the current time when presenting information (morning vs. afternoon focus)
  4. Actionable: Suggest next steps when appropriate
  5. Consolidate: Group related items together for clarity

Example Daily Summary Format

## Today's Overview

### Meetings (3)
- 09:00 - Standup (30m)
- 14:00 - Design Review with Product Team (1h)
- 16:00 - 1:1 with Manager (30m)

### Priority Tasks
🔴 OVERDUE: [Task description] (was due yesterday)
🟡 DUE TODAY: [Task description]
⭐ HIGH PRIORITY: [Task description]

### Needs Attention
- 5 unread emails (2 from this morning)
- JIRA-123: PR review requested
- Slack: @mentioned in #team-channel

### Suggested Focus
Based on your schedule, you have a 4-hour block this morning before your Design Review. Consider tackling [specific task] during this time.

Read the full file on GitHub · 92 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 92 lines · 24 tokens per session scan A 5803f9672bad

Subscribe to this mod's changes

assistant is an agent published in the GitHub repository adampoit/ai (2 stars, last pushed 7d ago), licensed MIT. It adds 24 tokens to every session and 653 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.