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Content-aware output compression for AI coding assistants. Replaces blind truncation with intelligent strategies per file type: structural summaries for code, schema extraction for configs, error-focused filtering for logs, and smart sampling for CSVs. Saves tokens while preserving what the model actually needs.
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Merge pull request #33 from ppgranger/fix/dedup-and-bugfixes
a5d068eView on GitHubMerge pull request #32 from ppgranger/fix/dedup-and-bugfixes
e4a66deView on GitHubMerge pull request #31 from ppgranger/feat/per-processor-disable-and-new-ecosystems
aa2b460View on GitHubfeat: add per-processor disable, 4 new processors, and multi-chain support
9bb49e2View on GitHubMerge pull request #30 from ppgranger/feat/new-processors-and-chaining
7fa15f0View on GitHubfix: resolve all ruff lint errors in new processors and tests
4e2b085View on GitHubfeat: add cargo, go, ssh, jq/yq processors and multi-processor chaining
5c8fe2bView on GitHubMerge pull request #28 from ppgranger/feat/processor-improvements
61c660fView on GitHubchore: bump version to 2.1.1, improve README marketing
9b89c76View on GitHubdocs: update README and add docs for new processors
3fe8678View on GitHubtest: add priority assertions and hook patterns for new processors
3491f5aView on GitHubfeat: allow local rsync through hook, exclude only remote rsync
1b0e108View on GitHub