context-optimization

Use context-mem to compress large tool outputs, search stored observations before re-reading files, and persist knowledge across sessions. Leverage its 14 content-aware summarizers (plus community plugins), 4-layer hybrid search (BM25 + Trigram + Levenshtein + Vector) with intent-aware adaptive reranking and block-level memory attention, cross-session memory, and cross-project knowledge transfer through 29 MCP tools. Dashboard receives real-time updates via WebSocket. Optional LLM enhancement (Ollama / OpenRouter / Claude API) is available when enabled — adds query expansion, smarter title/tag generation, contradiction explanation, and LLM summarization, all with deterministic fallback.

Core Tools

observe — After any large output (500+ tokens)

Store and compress content for later retrieval. Auto-summarizes based on content type. Built-in privacy engine auto-redacts secrets (AWS keys, GitHub tokens, JWTs, etc.) before storage.

observe(content: "<large output>", type: "log|code|error|test|commit|decision|context", source: "tool-name")

search — Before re-reading files

Search stored observations first. Adaptive reranking selects intent-specific weight vectors (causal / temporal / lookup / general) so results are scored differently based on what the query is asking. Block-level memory attention searches across four scope-based blocks (session, project, global, archive) using softmax attention to allocate the result budget, with per-block score normalization. Canonically identical queries return cached results (30s TTL).

search(query: "authentication error handler", type_filter: ["code", "error"], limit: 5)

get — After finding results via search

Retrieve full observation content by ID. Never guess IDs — always get them from search or timeline first.

get(id: "<observation-id-from-search>")

restore_session — At session start

Recover context from previous sessions. Session ID is optional — defaults to current session.

restore_session(session_id?: "<optional-specific-session>")

save_knowledge — For reusable patterns (with contradiction detection)

Store decisions, error fixes, API patterns. Auto-checks for contradictions via keyword overlap AND semantic vector similarity (when available). Note that knowledge entries decay in search ranking (14-day half-life) unless actively accessed. Explicit entries decay slower.

save_knowledge(category: "decision|error|pattern|api|component", title: "...", content: "...", tags: ["..."], source_type: "explicit|inferred|observed")

search_knowledge — Search the knowledge base

Search knowledge entries by query with optional category filter.

search_knowledge(query: "auth pattern", category?: "pattern", limit?: 10)

update_profile — Project quick profile

Update the 3-5 line project summary shown at every session start. Auto-generates from knowledge if no content provided.

update_profile(content?: "Tech: React Native\nFocus: insurance app")

budget_status — When context feels heavy

Check token usage. If over 80%, save work and call restore_session.

budget_status()

execute — Run code snippets

Execute code in 11 languages (JS, TS, Python, Shell, Ruby, Go, Rust, PHP, Perl, R, Elixir). Sandboxed with env sanitization.

execute(code: "console.log('hello')", language: "javascript")

emit_event / query_events — Event tracking

Log and query priority events (P1-P4) for session analysis.

emit_event(event_type: "error", data: { file: "auth.ts", message: "token expired" })
query_events(event_type?: "error", priority?: 1, limit?: 50)

time_travel — View/compare project state at any point in time

Parse relative dates ("3 days ago", "last week") or absolute timestamps. Compare then vs now to see what changed.

time_travel(target: "3 days ago")
time_travel(target: "2025-12-01", compare: true)

ask — Natural language questions about the project

Intent classification (what/when/who/why/how) with parallel search across knowledge, observations, events, and graph.

ask(question: "why did we switch from REST to GraphQL?")
ask(question: "what changed in the auth module last week?")

Additional Tools

• summarize — Compress content and return the summary without storing. Use when the result is needed inline but not for later retrieval (unlike observe which stores).
• timeline — Browse observations chronologically. Use anchor param to see context before/after a specific observation. Prefer over search when exploring what happened in sequence.
• stats — Token economy stats for the current session (observations stored, savings percentage, searches performed).
• configure — Update runtime config (e.g., configure(key: "privacy.strip_tags", value: false)). Changes persist for the session.
• index_content — Chunk and index source code for later search. Use on large files before searching them. Pairs with search_content.
• search_content — Search code previously indexed with index_content. Returns matching chunks with file context.
• budget_configure — Set session token limits and overflow strategy (warn, truncate, or block). Use at session start to set budget constraints.
• promote_knowledge — Promote a project knowledge entry to the global cross-project store. Privacy engine auto-redacts secrets before storing. Use for patterns that apply across multiple projects.
• global_search — Search the global cross-project knowledge store. Returns entries promoted from any project, with source project tracking.
• agent_register — Register current session as a named agent for multi-agent coordination. Provides identity for file claims and broadcasts.
• agent_status — List all active agents, their current tasks, and claimed files. Use to see what other agents are working on before starting a task.
• claim_files — Claim files being worked on to prevent conflicts with other agents. Detects and reports conflicts if another agent already claimed the same file.
• agent_broadcast — Send priority messages to all active agents via the event system. Use for important findings, blockers, or coordination signals.
• graph_query — Query entities and their relationships. Filter by entity type, relationship type, direction (in/out/both), and traversal depth (1-5).
• add_relationship — Create a relationship between two entities. Auto-creates entities if missing. Accepts optional weight (0-1).
• graph_neighbors — Find all entities connected to a given entity. Faster than graph_query for simple one-hop lookups.

Multi-Agent Coordination

When multiple agents work on the same project simultaneously:

• Register as a named agent when working on a specific task (agent_register)
• Claim files before editing to prevent conflicts (claim_files)
• Check agent_status to see what others are doing before starting work
• Broadcast important findings to all agents (agent_broadcast)

Rules

• ALWAYS search before get — never guess observation IDs
• ALWAYS observe outputs over 500 tokens — keep context clean
• NEVER call get without first finding the ID via search or timeline
• When budget_status shows >80%: save work, call restore_session
• When save_knowledge returns contradictions — review before proceeding, do NOT silently overwrite
• Use source_type when saving knowledge — trust: explicit > inferred > observed
• Expect knowledge entries to have relevance decay — frequently accessed entries stay relevant longer

Activity Journal

The PostToolUse hook automatically logs every edit, command, and file read to .context-mem/journal.md. This journal persists across sessions and is injected at session start for continuity.

Background Processes

The Dreamer background agent runs automatically (separate from the 14-day relevance-decay half-life used in search ranking):

• Marks knowledge entries as stale after 30 days without access
• Auto-archives non-explicit entries after 90 days
• Detects potential contradictions between entries in the same category
• Explicit (source_type: 'explicit') entries are never auto-archived

Dashboard 2.0

The dashboard now includes: knowledge graph visualization, timeline explorer, agent panel for monitoring multi-agent sessions, and dark theme support.

Priority Order

1. restore_session + budget_configure — at session start
2. search — before reading files
3. observe — after large outputs
4. save_knowledge — for decisions and patterns
5. update_profile — when project context changes significantly
6. budget_status — periodically when context grows