mpfaffenberger / mpfaffenberger/code_puppy

Feature Request: Display Active Agents’ Status in CLI

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enhancement
Dominant language
Python
Stars
814
Forks
278
Avg merge
2d 5h
Merged PRs (30d)
76

Description

Feature Request: Display Active Agents’ Status in CLI

Description
When Code Puppy is executing a task, the main agent can invoke several sub-agents to handle different parts of the workload.
Currently, when these agents are running, there’s no visible feedback in the CLI — making it difficult for the user to understand what’s happening in real time.

Problem
The lack of feedback leads to uncertainty about system activity. Users don’t know:

  • Which agents are currently active
  • Which models each agent is using
  • How many tokens each agent has consumed or is currently using

This makes debugging and monitoring complex tasks more difficult.

Proposed Solution
Add real-time feedback in the CLI showing all active agents besides the main one.
Each entry should display at least:

  • Agent name
  • LLM model in use
  • Total tokens (used + allocated)

Example (mockup):

[planning-agent]  GLM-4.6   tokens: 1200 / 200000 (10%)
[code-analyzer]  GPT-4o   tokens: 800 / 272000 (10%)
[test-runner]  Claude-3   tokens: 230 / 200000 (10%)

Implementation Suggestions

  • Add an internal event emitter or logging hook in the agent orchestration layer to track agent invocation and token usage.
  • Update the CLI renderer to display agent activity dynamically (e.g., refresh every few seconds or on status change).
  • Consider an optional flag (e.g., --verbose or --show-agents) to toggle this feature for users who prefer quieter output.

Expected Benefits

  • Better transparency into concurrent agent execution.
  • Easier performance tuning and debugging.
  • Enhanced user experience during long or complex operations.

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by locating the agent orchestration layer and the CLI renderer mentioned in the issue. Trace how agent invocations and token usage are currently represented, then determine the status information and display behavior needed for the requested feedback. Done means active sub-agents, models, and token totals are visible in the CLI during execution.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
ai, cli
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
35/100

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