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Activity Log

Community
jmagly
activity-log

Query and manage the unified .aiwg/activity.log chronological record of AIWG-managed workflow operations

Overview

Publisherjmagly
Repositoryaiwg
Skill nameactivity-log
Stars
225
Forks
34
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by jmagly on GitHub. Read the source before you install it.

Installation

Install the Activity Log AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/jmagly/aiwg/tree/main/agentic/code/addons/aiwg-utils/skills/activity-log
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/jmagly/aiwg.git /tmp/aiwg
mkdir -p .claude/skills
cp -r /tmp/aiwg/agentic/code/addons/aiwg-utils/skills/activity-log .claude/skills/activity-log
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Activity Log in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Activity Log on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Activity Log is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Activity Log

You query and manage the unified .aiwg/activity.log — a chronological record of all framework operations across SDLC, research, and other AIWG-managed workflows.

Triggers

Alternate expressions and non-obvious activations (primary phrases are matched automatically from the skill description):

  • "what happened recently" → show (default limit)
  • "show me today's activity" → show --since today's date
  • "log a create operation" → append create
  • "how many deploys have we done" → stats
  • "activity since last week" → show --since YYYY-MM-DD

Trigger Patterns Reference

PatternExampleAction
Recent activity"show activity log"activity-log show
Filtered by date"activity since 2026-04-10"activity-log show --since 2026-04-10
Filtered by operation"show all deploys"activity-log show --operation deploy
Limited output"last 5 entries"activity-log show --limit 5
Manual append"log that we archived the SAD draft"activity-log append archive <summary>
Statistics"how many operations by type"activity-log stats

Behavior

When triggered:

  1. Identify the subcommand:

    • show — display entries, optionally filtered
    • append — add a manual entry
    • stats — summarize operation counts and date range
  2. Locate the log file: .aiwg/activity.log relative to the project root. If the file does not exist, report it as empty (do not error).

  3. Execute the subcommand:

show

Display entries in reverse-chronological order (newest first).

bash
# Show last 20 entries (default)
aiwg activity-log show

# Filter by date (inclusive)
aiwg activity-log show --since 2026-04-10

# Filter by operation type
aiwg activity-log show --operation deploy

# Limit output count
aiwg activity-log show --limit 5

# Combine filters
aiwg activity-log show --since 2026-04-10 --operation create --limit 10

Accepted --operation values: ingest, create, update, delete, query, lint, deploy, archive, promote

append

Add a manual entry with the current UTC timestamp.

bash
# Append a manual entry
aiwg activity-log append <operation> "<summary>"

Example:

bash
aiwg activity-log append create "UC-011-logout.md created manually during team review"

The entry is written in standard format:

## [2026-04-12 14:33] create | UC-011-logout.md created manually during team review

Reject invalid operation tokens with a clear error listing the nine valid tokens.

stats

Summarize operation counts grouped by type and show the date range covered.

bash
aiwg activity-log stats

Output format:

Activity Log Statistics
Log file: .aiwg/activity.log
Date range: 2026-04-01 → 2026-04-12 (12 days)
Total entries: 47

By operation:
  create    18  ████████████████████  38%
  update    12  █████████████         26%
  deploy     7  ████████               15%
  archive    4  ████                    9%
  lint       3  ███                     6%
  promote    2  ██                      4%
  delete     1  █                       2%

Examples

Example 1: Recent activity overview

User: "What's happened in the activity log recently?"

Extraction: show subcommand, default limit

Action:

bash
aiwg activity-log show --limit 10

Response: Last 10 entries from .aiwg/activity.log newest first. If the file is absent, report "No activity log found at .aiwg/activity.log — operations will create it automatically."

Example 2: Audit all deploys

User: "Show me all deploy operations since April 10th"

Extraction: show, --operation deploy, --since 2026-04-10

Action:

bash
aiwg activity-log show --operation deploy --since 2026-04-10

Response: Filtered entries matching deploy on or after 2026-04-10, newest first.

Example 3: Manual log entry

User: "Log that we archived the old SAD draft"

Extraction: append, operation = archive, summary from user phrase

Action:

bash
aiwg activity-log append archive ".aiwg/working/sad-draft-v0.1.md archived manually after SAD baseline"

Response: "Entry appended to .aiwg/activity.log."

Example 4: Operation statistics

User: "Give me a stats breakdown of the activity log"

Extraction: stats subcommand

Action:

bash
aiwg activity-log stats

Response: Tabular summary with operation counts, percentages, and date range.

Clarification Prompts

If the user's intent is ambiguous:

  • "Are you looking to read recent activity or record a new entry?"
  • "Which operation type should I filter on? Valid types: ingest, create, update, delete, query, lint, deploy, archive, promote."

Storage routing

aiwg activity-log routes through resolveStorage('activity_log') (#964). On the default fs backend, the log file is .aiwg/activity.log and the line format is byte-identical to the legacy echo >> .aiwg/activity.log pattern. Configuring .aiwg/storage.config redirects the log to a different filesystem location (via roots.activity_log) without changing how agents call the CLI.

References

  • @$AIWG_ROOT/agentic/code/addons/aiwg-utils/rules/activity-log.md — Rule that governs when agents must append entries
  • @$AIWG_ROOT/agentic/code/addons/aiwg-utils/skills/index/SKILL.md — Artifact index skill (complementary query tool)
  • @$AIWG_ROOT/.aiwg/architecture/storage-design.md — Storage adapter design (#934)
  • @$AIWG_ROOT/docs/cli-reference.md — CLI reference

Frequently asked questions

What does the Activity Log AI skill do?

Query and manage the unified .aiwg/activity.log chronological record of AIWG-managed workflow operations

Why use Activity Log on TypingMind?

Because you install it once and use it with any model. Activity Log is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Activity Log in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jmagly/aiwg/tree/main/agentic/code/addons/aiwg-utils/skills/activity-log. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Activity Log?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Activity Log?

As many as you like. As long as a model supports skills, you can use Activity Log with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Activity Log AI skill free?

Yes. It is published on GitHub by jmagly under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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