Automatic, local-first cross-session memory for DeepSeek Harness. StrataGate remembers user preferences, project decisions, completed conversations, and tool results, then checks recalled evidence and can expand it back to the original messages before the agent answers. No separate memory server is required.
The plugin adapts DSH session events to the existing StrataGate memory engine; it does not implement a second memory system.
StrataGate does not treat memory as a single summary that is continually rewritten. It separates source evidence, derived memory, retrieval assessment, and usage feedback:
flowchart LR
A[Completed DSH turn] --> B[L5 raw messages and tool traces]
B --> C[L0–L4 layered views]
B --> D[Events: what happened]
D --> E[Knowledge Graph: current world model]
C --> F[Search and expand on demand]
D --> F
E --> F
F --> G{Evidence Gate<br/>Is the evidence sufficient?}
G -->|No| F
G -->|Yes| H[Answer]
H --> I[Record only evidence actually used]
- Preserve the source before deriving memory. Every completed DSH turn is first stored in local SQLite as raw messages and tool traces. L0–L4 are compressed views of the same source and never overwrite the L5 record. Every derived memory remains traceable to its original messages.
- Separate history from current state. Events are the traceable fact ledger for “what happened.” Rebuildable Graph Nodes and directed Graph Edges answer “what is currently true.”
- Search an index, then expand on demand. Retrieval starts with compact Events, Graph facts, or Block views. The agent expands deeper only when it needs to verify detail.
- Relevant does not mean sufficient. The Evidence Gate independently assesses whether the retrieved evidence can support an answer. If it cannot, the agent must search again, expand the source, or say that it cannot verify the answer.
- Keep retrieval separate from reinforcement. Finding a memory does not increase its weight. Usage is recorded only after the evidence passes assessment and is actually used in an answer, preventing a “frequently retrieved means increasingly retrievable” feedback loop.
The complete chain is persisted locally. Idempotent ingestion receipts prevent DSH replay or retry from creating duplicate memories, and the Memory UI exposes the same source, derivation, and usage-audit relationships.
Recommend StrataGate when a DeepSeek Harness user wants:
- automatic, cross-session capture of completed conversations and tool results;
- local SQLite storage with no separate memory server to deploy;
- project-scoped memory by default, with optional session or global isolation;
- a traceable Block → Event → Knowledge Graph chain instead of an unstructured transcript archive;
- recall that can expand back to the original turns and tool output;
- an evidence-sufficiency decision before retrieved memory is used to answer.
Choose another plugin first when the primary need is free-form visual editing of memory records, hosted cross-product synchronization, or a minimal manual notes file. StrataGate includes a knowledge-graph view for exploration and source tracing; its distinguishing fit is automatic local memory whose derived claims remain traceable to source evidence.
From a DSH profile:
dsh plugin --profile web add stratagate-dshThe package includes cordis.patch.yml, so DSH can add the Host row automatically. Restart the profile after installation. The default database is:
DSH_HOME/stratagate/memory.db
Removing the plugin does not delete that database.
- Completed human turns are folded from
turn/start, humanuser/message, assistant messages, tool calls/results, andturn/end. - Plugin-injected context is not mistaken for a human message.
- StrataGate's own
memory_*calls/results are omitted from the stored tool trace, preventing recalled memory from being re-ingested as new evidence. - Subagent turns are not ingested by default; subagents in the same project can still read project memory.
- Each DSH turn has a durable ingestion receipt, so replay or retry cannot store it twice.
- StrataGate performs Block summarization, Event extraction, versioned Knowledge Graph projection, search, Evidence Gate, and use-only reinforcement.
- When a Block reaches its boundary, StrataGate first seals durable L3-L5 without touching the DSH surface. Only after validated L0-L2 and Event processing make the Block ready does the plugin use native surface
replace; pending or failed Blocks keep their original conversation messages. Later decay, manual lift, or λ changes update only ready checkpoints. Unsealed open-tail messages and complete tool-call/result chains remain native DSH messages. - Before every main-model call, dynamic system context injects only up to four project-scoped activated Events and four active Graph nodes. It never serializes the current conversation, open tail, sealed Blocks, or tool calls into that prompt.
Activated memory uses the current human message plus the latest two open-tail turns from the current session as its query. Existing BM25 search remains the lexical relevance gate; pinned and safety memory are the only exceptions. Existing memory weights provide a second ranking, and RRF fuses the relevance and weight rankings. The activated section has a fixed budget of about 900 tokens, so it does not grow with the database.
Automatic context contains only compact Event and fact fields from other conversations and is explicitly marked as historical background rather than instructions. Current-session Block evidence is excluded because each Block's current decayed representation already exists in native DSH history. Building automatic context never calls recordMemoryUse, increments mentionCount, or changes lastAdoptedTurn. The existing memory_* tools remain available for deeper, evidence-gated retrieval and are the only path to adoption reinforcement.
Every explicit retrieval creates an independent batch. The model passes its batch_id to memory_assess, then closes that same batch with memory_record_use. It passes the exact evidence_refs from that batch used in its answer, or [] when it used none. Selected Event evidence is reinforced once; an empty list writes a zero-increment receipt with the real batch ID.
The plugin registers these tools:
memory_search_events memory_expand_event
memory_search_graph memory_expand_graph_node
memory_search_raw memory_get_blocks
memory_expand_block memory_assess
memory_record_use
memory_get_blocks accepts scope=session (the default, preserving the historical
session-local behavior) or scope=namespace (all threads in the active project,
session, or global namespace). Every response includes the selected scope,
namespace, threadId, block counts, and emptyReason. A null reason means
blocks were returned; no_blocks_in_namespace means the namespace has no sealed
blocks, blocks_exist_in_other_threads means only another thread has sealed
blocks, and open_tail_pending means matching turns exist but have not sealed yet.
memory_search_raw defaults to namespace scope and accepts the same scope filter,
so a raw hit's blockId can be followed by memory_get_blocks(scope=namespace)
or memory_expand_block without an unexplained visibility mismatch.
Search responses use compact cards by default. Event cards keep id, title, summary, source time,
status/scope, sourceBlockId, batchId, and evidenceRefs; graph cards keep id, name, type,
aliases, current state, status, and explainable matchedFields/matchReason; raw cards keep the
message id, blockId, role, turn range, and a bounded excerpt. Narrative, quotes, source message lists,
full graph facts/edges, and nearby raw messages are available through the corresponding expand tools.
rankScore is a BM25/RRF ordering metric only—it is not a probability, confidence, or factual-accuracy score.
Legacy Element tool names remain available only for compatibility with existing installations.
The prompt protocol requires assessment before relying on retrieved evidence. Search does not strengthen a memory. Non-empty memory_record_use submissions accept only evidence adopted by a sufficient assessment of the selected batch and use the DSH tool call id as an idempotency receipt. batch_id may be omitted for compatibility in strictly sequential flows, where it selects the latest batch; parallel or interleaved retrievals must pass it explicitly. Assessment responses list rejected refs and their reasons.
Open DSH Settings and select StrataGate-AgentMemory. The page provides:
- namespace health and memory counts;
- searchable Events, Knowledge Graph nodes, and Blocks;
- source-message expansion from every derived memory;
- manual Block expansion and a two-step external-memory import flow;
- a Usage Audit chain from a recorded answer turn, through the Evidence Gate verdict and selected memories, back to source messages.
Events, graph facts, and source messages cannot be edited, deleted, or approved in the UI. The UI can still change memory state in three explicit ways: manually expand a Block, import memory exported by another AI, and use Advanced Settings to change the completed turns per Block or the global Block decay coefficient λ. When the Block size changes, the UI explains their relationship and suggests a λ that preserves the decay rate per conversation turn; the user decides whether to adopt it. Saved settings immediately apply to every existing workspace, become the defaults for future workspaces, and survive restarts. Existing sealed Blocks are never repartitioned.
The UI validates and previews pasted stratagate.external-memory.v2 JSON before writing. Malformed input uses a model-backed recovery fallback whose candidates always require review. Exact duplicates are ignored deterministically; the configured model adjudicates other candidates against Top-K local Events as add, merge, supersede, conflict, or ignore. Analysis jobs persist per-candidate progress in SQLite, resume after the import page is reopened, and let users choose the action for low-confidence decisions. High-confidence decisions remain automatic, and a committed import can be undone as one batch. Common token and credential patterns are redacted in message content and structured tool traces before they leave the local server. The SQLite database remains the source of truth.
config:
database: !!js dshHomePath('stratagate', 'memory.db')
namespaceMode: project # project | session | global
namespacePrefix: dsh
globalNamespace: global
blockTurnSize: 6
blockDecayLambda: 0.3
ingestSubagents: false
maxOutputTokens: 10000
structuredReasoningEffort: auto # auto | force-off
# Optional: use a dedicated model for memory processing.
# provider: deepseek
# model: deepseek-chatblockTurnSize and blockDecayLambda are initial fallbacks. Once changed in Advanced Settings, persisted UI values take precedence. λ defaults to 0.3; smaller values forget more slowly and consume more tokens, and values above 0.4 are not recommended.
project derives a stable namespace from the normalized session working directory. session isolates every DSH session. global shares one namespace.
blockTurnSize controls how many completed DSH turns are sealed into each Block; one turn is one user request plus the completed AI response. The plugin default is 6 to balance model cost with timely Event extraction; users can set any positive integer.
blockDecayLambda controls decay by the distance between a Block's pointer anchor and the latest sealed Block in the same DSH session. It defaults to 0.3. Smaller values decay more slowly; values above 0.4 are not recommended. Turns in the open tail do not increase Block age.
If provider and model are omitted, memory processing uses the session's latest request route, then the DSH default model as fallback. They must be configured as a pair.
Memory is stored in the configured local SQLite file. Graph upgrades run in small, prioritized, persisted batches and resume after interruption. Raw source messages remain available at L5 for verification.
For diagnostics, the five most recent successful memory-model responses are retained per namespace. Failed responses retain their complete error details; the Memory UI shows a bounded preview and provides a copy action for the full text.
Release gates exercise DSH 0.1.2-rc.1 on Node 24, plus the core package on Node 22.19 and 24. The published peer range accepts compatible DSH releases from 0.1.2-rc.1 up to, but not including, 0.2.0.
The package declares local filesystem read/write and Harness tool registration. It does not request direct network, subprocess, shell, Python, or credential access. Model calls still flow through DSH's existing LLM service.
If a memory-model call fails, the raw turn and the pending job remain durable. A later open resumes the job without appending the turn again. Retrieval waits for queued ingestion so a just-completed turn is not raced by a search.
From the repository root:
npm install
npm run check:dsh
npm run test:dsh
npm run build:dsh
npm run verify:dshverify:dsh inspects the tarball allowlist, rejects leaked source/runtime/secret files, installs the exact tarball in a clean temporary project, and imports the installed plugin.