This release adds 2 notable features for engineering teams evaluating rollout.
✓ No known CVEs patched in this version
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Summary
AI summaryEnriched MCP tool metadata with explicit behavior, idempotency, side-effect, purpose, usage guidance, state-change semantics, and parameter constraints to improve Glama scoring.
Full changelog
Summary\nThis release improves MCP tool metadata quality for Glama scoring and agent usability.\n\n## Changes\n- Enriched tool metadata with explicit behavior, idempotency, side-effect, and usage guidance.\n- Enriched tool metadata with clearer purpose, scoped usage guidance, and parameter semantics.\n- Enriched tool metadata with explicit state-change semantics, side-effect expectations, and parameter constraints.\n- Added MCP annotations for all three tools: , , , .\n- Added schema-level parameter descriptions and basic constraints/defaults to improve first-attempt tool-call reliability.\n\n## Motivation\nGlama code-quality checks flagged low completeness/usage guidance for tool descriptions despite successful runtime builds. This patch addresses those rubric gaps directly.\n\n## Included PR\n- https://github.com/sheawinkler/ContextLattice/pull/142\n\n## Deterministic target\n- Commit:
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About sheawinkler/ContextLattice
Private-by-default memory and context layer for agents with Go/Rust runtime, staged retrieval across fused data backends, and long-horizon context continuity.
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Beta — feedback welcome: [email protected]