My Claude Bot
C 68 completed
Other
library / python · small
62
Files
7,158
LOC
1
Frameworks
4
Languages
Pipeline State
completedRun ID
#1545906Phase
doneProgress
0%Started
2026-04-16 23:37:16Finished
2026-04-16 23:37:16LLM tokens
0Pipeline Metadata
Stage
CatalogedDecision
proceedNovelty
34.27Framework unique
—Isolation
—Last stage change
2026-05-10 03:34:57Deduplication group #49631
Member of a group with 130 similar repo(s) — canonical #1566776 view group →
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🧪 Code Distillation
Browse all specs →AI Prompt
Create a multi-agent Telegram platform using Python. I need a system that supports a fleet of AI agents, each with its own bot and skills. Key features should include an asynchronous MessageBus for inter-agent communication, streaming responses to Telegram, and a background 'Dream Memory' for fact extraction and wiki updates. It must also handle periodic tasks via cron jobs, integrate with external services like Todoist and GitHub via MCP servers, and support analyzing uploaded files and photos. Please ensure it can handle group chats with isolated memory and support voice message transcription using the Deepgram API.
python telegram multi-agent ai messaging docker pytest api automation
Generated by gemma4:latest
Catalog Information
Create a multi-agent Telegram platform using Python. I need a system that supports a fleet of AI agents, each with its own bot and skills. Key features should include an asynchronous MessageBus for inter-agent communication, streaming responses to Telegram, and a background 'Dream Memory' for fact extraction and wiki updates. It must also handle periodic tasks via cron jobs, integrate with external services like Todoist and GitHub via MCP servers, and support analyzing uploaded files and photos.
Tags
python telegram multi-agent ai messaging docker pytest api automation
Quality Score
C
68.2/100
Structure
72
Code Quality
65
Documentation
65
Testing
70
Practices
61
Security
82
Dependencies
90
Strengths
- Good test coverage (68% test-to-source ratio)
- Consistent naming conventions (snake_case)
- Good security practices — no major issues detected
- Containerized deployment (Docker)
- Properly licensed project
Weaknesses
- No CI/CD configuration — manual testing and deployment
- Potential hardcoded secrets in 1 files
- 440 duplicate lines detected — consider DRY refactoring
- 1 'god files' with >500 LOC need decomposition
Recommendations
- Set up CI/CD (GitHub Actions recommended) to automate testing and deployment
- Add a linter configuration to enforce code style consistency
- Move hardcoded secrets to environment variables or a secrets manager
Languages
Frameworks
pytest
Symbols
method96
function81
variable36
constant24
class13
property2
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BinComp Dependency Hardening
All packages →2 of this repo's dependencies have been scanned for binary hardening. Grade reflects RELRO / stack canary / FORTIFY / PIE coverage.