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Goose Compaction: Why One 27B Model Re-read a File in 95% of Trials

One local 27B model reread an already supplied file in 19 of 20 pre-change trials after Goose compaction. Retaining recent tool messages reduced redundant reads in the author’s test, with important caveats.
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In a small experiment reported by Mihai Perdum, a local Qwen3.6 27B model’s first action after Goose conversation compaction was to read a file it had already seen in 19 of 20 trials. Keeping recent tool messages in their original conversational positions reduced first-action reads to 3 of 20—and none of those three reread the supplied file. The result is an intriguing implementation report, not evidence that all 27B models or coding agents behave this way.

What the 95% figure means

The 95% is 19 first-action reads across 20 trials in the author’s pre-change condition. It is not a measured rate for Goose users generally, nor a claim about every 27B model. The reported test involved one local model and one compaction setup.

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Perdum describes Goose as summarizing a conversation after it crosses a token threshold, then hiding earlier messages from the agent while leaving them in the session transcript. The concern is that a summary may preserve conclusions while dropping useful interaction history: tool requests, file contents returned by tools, and test output. Once that context is no longer visible to the agent, it may request a file again.

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How the three approaches compared

The article reports 20 samples per condition at temperature 0.7. Its table gives prompt lengths and first-action read counts as follows:

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Compaction approach First action was a read Prompt length What remained available
Pre-change behavior, without a retained tool tail 19/20 (95%) 159 tokens No recent tool-message tail was retained.
File contents quoted in summary prose 18/20 (90%) 217 tokens The file bytes appeared in the summary, rather than as the original tool messages.
Recent tool-message tail retained in its original position 3/20 (15%); none reread the already supplied file 283 tokens Recent messages, including tool traffic, were preserved in their original conversational positions.

In the retained-tail condition, the three reads were for a test file the model had not been shown. That distinction matters: a read is not necessarily redundant. The notable result is that none of those reads fetched the already supplied file again.

Why preserving message position may matter

The comparison suggests that simply inserting file contents into summary prose did not reproduce the behavior seen when recent tool messages were retained in place. The prose-summary control included the same file bytes as the retained-tail condition, yet its first-action read count was close to the pre-change result. Perdum’s interpretation is that the original position and form of tool messages may matter, but the experiment does not establish why.

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There is also an important confound: the retained-tail prompts were longest at 283 tokens, compared with 159 and 217 in the other conditions. The author acknowledges that prompt length could have affected the result. The small sample cannot isolate the effect of message position from every other difference.

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What the proposed Goose change does

Perdum describes a setting named GOOSE_COMPACT_KEEP_TAIL. The proposed behavior is to summarize earlier messages and append a recent tail without rewriting those messages, preserving their place and format in the conversation. The account says the intended default is zero, which would retain the prior behavior.

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A tail cannot safely be chosen as a blind fixed-length slice. If the cutoff lands between a tool request and its response, the retained conversation could begin with a response whose initiating request is missing. The described implementation walks the cutoff backward to include the associated request. It also avoids adding a preserved user message twice when that message already falls within the retained tail.

The author reports comparing serialized outputs after normalizing timestamps to check that a zero setting preserves old behavior. That is the author’s reported check, not independent verification. The setting and implementation details should be confirmed against the particular Goose fork and version in use; the cited account does not establish that the setting is available in every installation.

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How far the result can be generalized

The reported setup was a Mac Studio M3 Ultra with 96 GB of memory, running Qwen3.6-27B-Fable-Fusion-711 Heretic NEO MAX MTP at Q8_0 through llama.cpp’s llama-server. This describes one local configuration. The author did not report comparisons across other models, hardware, compaction implementations, or workloads, and did not test a frontier model.

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The author also says a registered run-level test comparing file rereads in a post-compaction swarm run had not yet been run. So the evidence is a controlled probe of first actions, not proof that the change improves complete coding runs in production.

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What to check if your agent keeps rereading files

Repeated reads after compaction are a useful signal to inspect what context the agent actually receives, rather than assuming it has access to everything still visible in a session transcript. Check whether the relevant file contents and tool exchange survive in the compacted prompt, and whether the retained history keeps tool requests paired with their responses.

If considering a retained-tail setting, first verify the exact option and default in your Goose version or fork. Then test the behavior on your own workload: compare the post-compaction prompt and the agent’s actions, and distinguish a redundant reread from a legitimate request for a file that was never supplied. The reported counts can motivate that check, but they do not predict its outcome for another model or system.

Sources

The retrieved pages did not establish an exact publication date. The figures above are therefore presented as the author’s reported measurements, not independently reproduced findings.

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