anthropics / anthropics/claude-code
[Feature Request] Add model performance monitoring and transparent API behavior documentation
- Dominant language
- Python
- Stars
- 145k
- Forks
- 23.1k
- PR merge metrics
- PR metrics pending
Description
## Summary
When a newer model is released, older models (in this case Sonnet 5) appear to degrade sharply. I spent 4–5 hours stuck on a simple bug with Sonnet 5. Switching to Fable resolved it immediately.
If this is intentional routing or quality throttling, it is opaque and feels like a way to burn extra tokens. Please document expected model behavior and add a way to monitor quality regressions.
I have used Sonnet for more than six months across multiple accounts.
## What happened
1. I was debugging a simple issue in Claude Code using Sonnet 5.
2. The model looped, repeated itself, and failed to make progress for 4–5 hours.
3. I switched the model to Fable.
4. The same task completed successfully.
## Why this matters
- Large token spend with no useful output
- No signal that the model is underperforming
- No public documentation of how older models change after a new release
- Hard to trust Claude Code for production work if quality can drop without notice
## Requested outcome
- Transparent documentation of model versions, routing, and any known quality changes after a new release
- In-product monitoring or a warning when a session is looping / not making progress
- A way to pin a known-good model version so behavior does not silently change
- Confirmation that older models are not intentionally degraded
## Environment
- Platform: darwin
- Terminal: iTerm.app
- Version: 2.1.274
- Feedback ID: b0777965-efe8-403e-9a8b-e7b6e2c22a85
## Errors
```json
[]
Contributor guide
No contributing guide indexed for this repository
Research direction
No files, tests, or entry points are named. Start by separating the requested documentation, quality-regression monitoring, looping warning, and model pinning into scoped requirements. Done should define supported model behavior and version semantics plus a testable monitoring or warning outcome, but the issue does not identify implementation locations.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- ai, cli, documentation, observability
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Active
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100