This release adds 3 notable features for engineering teams evaluating rollout.
✓ No known CVEs patched in this version
Topics
+14 more
Summary
AI summaryUpdates Testing, Two new MCP tools, and README across a mixed release.
Full changelog
v5.15.0 — Context Signal-Over-Noise
Agents have large context windows, but their effective reasoning window is smaller: irrelevant, stale, or noisy context degrades output quality long before the hard token limit ("context rot"). This release makes curated context a first-class primitive.
ContextComposer (lib/context-composer.ts)
Token-budgeted, relevance-ranked context assembly for any LLM call:
- Ranking — every candidate entry is scored by relevance (pluggable BYOE
SemanticRankerwith a deterministic lexical-overlap fallback) x recency (exponential half-life decay) x scope affinity (ContextThrottlertag semantics). - Hard token budget — enforced via the new zero-dependency
estimateTokens()heuristic; over-budget items are excluded with reasons. - Pinned sources — task-critical instructions and Layer-3 project context always lead the pack.
- Staleness — TTL-expired entries are dropped automatically.
- Position-aware layout — strongest items placed first and last ("lost in the middle" mitigation), serpentine ordering in between.
- Full observability — included/excluded lists with per-item scores, token costs, and budget utilization.
createSemanticMemoryRanker()adapts an existingSemanticMemory;ContextComposer.fromSnapshot()converts blackboard snapshots.
Two new MCP tools (lib/mcp-tools-context.ts, registered by default — 24 tools total)
context_pack— "give me everything relevant to task X in <= N tokens": one call returns a curated, ranked, budget-enforced context brief from the agent's scoped blackboard snapshot. Use instead ofblackboard_list+ manyblackboard_readcalls.blackboard_search— ranked top-K search over blackboard entries; semantic when aSemanticMemoryis wired, lexical otherwise (mode reported in the response).
Works out of the box in Claude Code, OpenAI Codex, Gemini CLI, Cursor, and any other MCP client.
Testing
- New
test-phase19.ts(78 assertions): token estimation, ranking/budget/pinning/staleness/serpentine layout, semantic-ranker integration + failure fallback, both MCP tools including scoped snapshots and argument validation. - Full suite: 3,603 tests passing across 40 suites;
tsc --noEmitclean.
Docs
- README: context feature bullet, MCP tools list, test table, Gemini CLI callout, AGENTS.md row.
- Consistency sweep: stale test counts fixed in CONTRIBUTING.md and SUPPLY_CHAIN.md;
claude-project-prompt.mdbanner updated; SECURITY.md supported-versions tables move 5.15.x to current.
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About Jovancoding/Network-AI
Multi-agent orchestration MCP server with race-condition-safe shared blackboard. 20+ MCP tools: blackboard read/write, agent spawn/stop, FSM transitions, budget tracking, token management, and audit log query. `npx network-ai-server --port 3001`.
Related context
Beta — feedback welcome: [email protected]