Compaction obscures session context and silently drops prior work #5799
Replies: 3 comments
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these are good thoughts. I have noticed similar behaviors also! |
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I've encountered a similar situation where, after the compression is triggered, the recent conversation history is discarded, and it returns to the user's original prompt to start processing the already completed task. |
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I wanted to update the discussion since codex has addressed some of the compaction behavior in the latest updates. A rundown of what changed, what it means in practice, and what that means within the scope of this discussion: What changed since v0.50.0
How to use the new settingsAdd these to your Codex config (in the profile you use). Exact layout may vary in your setup, but the keys are: Example: set a custom compact prompt inline [profile.my-workflow]
compact_prompt = """
Summarize for the next agent:
- Completed steps (with file paths)
- Outstanding TODOs (file:line) and blockers
- Decisions taken (why) and constraints (env/latency/tokens)
- What not to redo (explicitly list finished items)
One screen of bullets; be concise.
"""Example: load the prompt from a file [profile.my-workflow]
experimental_compact_prompt_file = "compact_prompt.txt"How the changes stack up against the original concerns
What’s still on the wish list (to be discussed)
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The current compaction flow rewrites history so aggressively that it obscures the overall framing. The new inline auto-compaction just makes it even harder to notice. I’d like to gather experiences + ideas before proposing changes.
What’s happening
/compactand for the auto version.model_auto_compact_token_limitto a massive number inconfig.toml, which isn’t documented and disables the safety entirely rather than just the mid-turn behavior.Why it matters
Possible directions
I don’t have the perfect resolution, but here are a few ideas that might be worth exploring:
/compact.Curious to hear whether others have run into similar issues or have ideas for balancing safety vs. autonomy. Even incremental transparency might help, but it feels like we need a broader rethink of how compaction behaves, especially now that it can trigger mid-turn without any user input.
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