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goclaw/docs/06-store-data-model.md
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- Dialogs: standardize scroll pattern across all modals — header fixed,
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- Add 10 missing internal modules to CLAUDE.md project structure
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- Add 8 missing store interfaces to data model docs (22 total)
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- Remove all references to removed features: handoff, delegate_search, evaluate_loop, agent_links
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29 KiB

06 - Store Layer and Data Model

The store layer abstracts all persistence behind Go interfaces backed by PostgreSQL. Each store interface has a PostgreSQL implementation wired at startup.


1. Store Layer

flowchart TD
    START["Gateway Startup"] --> PG["PostgreSQL Backend"]

    PG --> PG_STORES["PGSessionStore<br/>PGMemoryStore<br/>PGCronStore<br/>PGPairingStore<br/>PGSkillStore<br/>PGAgentStore<br/>PGProviderStore<br/>PGTracingStore<br/>PGMCPServerStore<br/>PGCustomToolStore<br/>PGChannelInstanceStore<br/>PGConfigSecretsStore<br/>PGTeamStore<br/>PGBuiltinToolStore<br/>PGPendingMessageStore<br/>PGKnowledgeGraphStore<br/>PGContactStore<br/>PGActivityStore<br/>PGSnapshotStore<br/>PGSecureCLIStore<br/>PGAPIKeyStore"]

2. Store Interface Map

The Stores struct is the top-level container holding all PostgreSQL-backed storage implementations.

Interface Implementation Purpose
SessionStore PGSessionStore Conversation history with in-memory write-behind cache
MemoryStore PGMemoryStore Memory documents, embedding, FTS, hybrid search (tsvector + pgvector)
CronStore PGCronStore Scheduled job definitions and execution logs
PairingStore PGPairingStore Browser pairing codes and paired device tracking
SkillStore PGSkillStore SKILL.md definitions, BM25 search, agent/user grants
AgentStore PGAgentStore Agent definitions, soft delete, RBAC sharing, access control
ProviderStore PGProviderStore LLM provider configs, encrypted API keys, model listings
TracingStore PGTracingStore LLM call traces, spans, observability aggregation
MCPServerStore PGMCPServerStore MCP server configs, transport (stdio/sse), tool grants
CustomToolStore PGCustomToolStore Dynamic tool definitions, shell command templates, agent/global scoping
ChannelInstanceStore PGChannelInstanceStore Channel instance configs (Telegram account, Discord guild, etc.)
ConfigSecretsStore PGConfigSecretsStore Encrypted configuration secrets (AES-256-GCM)
TeamStore PGTeamStore Teams, tasks (atomic claim), members, messages, delegation history
BuiltinToolStore PGBuiltinToolStore System tool metadata, enable/disable toggles, settings
PendingMessageStore PGPendingMessageStore Offline group chat message queue, auto-compaction to summaries
KnowledgeGraphStore PGKnowledgeGraphStore Entity-relationship graphs, traversal, inference extraction
ContactStore PGContactStore Channel contacts (auto-collected), cross-channel deduplication, merge
ActivityStore PGActivityStore Audit logs, action tracking, compliance
SnapshotStore PGSnapshotStore Hourly usage snapshots, cost aggregation, time series queries
SecureCLIStore PGSecureCLIStore CLI binary configs with encrypted credential injection
APIKeyStore PGAPIKeyStore Gateway API keys, scopes, expiration, revocation

3. Session Caching

The session store uses an in-memory write-behind cache to minimize database I/O during the agent tool loop. All reads and writes happen in memory; data is flushed to the persistent backend only when Save() is called at the end of a run.

flowchart TD
    subgraph "In-Memory Cache (map + mutex)"
        ADD["AddMessage()"] --> CACHE["Session Cache"]
        SET["SetSummary()"] --> CACHE
        ACC["AccumulateTokens()"] --> CACHE
        CACHE --> GET["GetHistory()"]
        CACHE --> GETSM["GetSummary()"]
    end

    CACHE -->|"Save(key)"| DB[("PostgreSQL")]
    DB -->|"Cache miss via GetOrCreate"| CACHE

Lifecycle

  1. GetOrCreate(key): Check cache; on miss, load from DB into cache; return session data.
  2. AddMessage/SetSummary/AccumulateTokens: Update in-memory cache only (no DB write).
  3. Save(key): Snapshot data under read lock, flush to DB via UPDATE.
  4. Delete(key): Remove from both cache and DB. List() always reads directly from DB.

Session Key Format

Type Format Example
DM agent:{agentId}:{channel}:direct:{peerId} agent:default:telegram:direct:386246614
Group agent:{agentId}:{channel}:group:{groupId} agent:default:telegram:group:-100123456
Subagent agent:{agentId}:subagent:{label} agent:default:subagent:my-task
Cron agent:{agentId}:cron:{jobId}:run:{runId} agent:default:cron:reminder:run:abc123
Main agent:{agentId}:{mainKey} agent:default:main

4. Agent Access Control

Agent access is checked via a 4-step pipeline.

flowchart TD
    REQ["CanAccess(agentID, userID)"] --> S1{"Agent exists?"}
    S1 -->|No| DENY["Deny"]
    S1 -->|Yes| S2{"is_default = true?"}
    S2 -->|Yes| ALLOW["Allow<br/>(role = owner if owner,<br/>user otherwise)"]
    S2 -->|No| S3{"owner_id = userID?"}
    S3 -->|Yes| ALLOW_OWNER["Allow (role = owner)"]
    S3 -->|No| S4{"Record in agent_shares?"}
    S4 -->|Yes| ALLOW_SHARE["Allow (role from share)"]
    S4 -->|No| DENY

The agent_shares table stores UNIQUE(agent_id, user_id) with roles: user, admin, operator.

ListAccessible(userID) queries: owner_id = ? OR is_default = true OR id IN (SELECT agent_id FROM agent_shares WHERE user_id = ?).


5. API Key Encryption

API keys in the llm_providers and mcp_servers tables are encrypted with AES-256-GCM before storage.

flowchart LR
    subgraph "Storing a key"
        PLAIN["Plaintext API key"] --> ENC["AES-256-GCM encrypt"]
        ENC --> DB["DB: 'aes-gcm:' + base64(nonce + ciphertext + tag)"]
    end

    subgraph "Loading a key"
        DB2["DB value"] --> CHECK{"Has 'aes-gcm:' prefix?"}
        CHECK -->|Yes| DEC["AES-256-GCM decrypt"]
        CHECK -->|No| RAW["Return as-is<br/>(backward compatibility)"]
        DEC --> USE["Plaintext key"]
        RAW --> USE
    end

GOCLAW_ENCRYPTION_KEY accepts three formats:

  • Hex: 64 characters (decoded to 32 bytes)
  • Base64: 44 characters (decoded to 32 bytes)
  • Raw: 32 characters (32 bytes direct)

Memory search combines full-text search (FTS) and vector similarity in a weighted merge.

flowchart TD
    QUERY["Search(query, agentID, userID)"] --> PAR

    subgraph PAR["Parallel Search"]
        FTS["FTS Search<br/>tsvector + plainto_tsquery<br/>Weight: 0.3"]
        VEC["Vector Search<br/>pgvector cosine distance<br/>Weight: 0.7"]
    end

    FTS --> MERGE["hybridMerge()"]
    VEC --> MERGE
    MERGE --> BOOST["Per-user scope: 1.2x boost<br/>Dedup: user copy wins over global"]
    BOOST --> FILTER["Min score filter<br/>+ max results limit"]
    FILTER --> RESULT["Sorted results"]

Merge Rules

  1. Normalize FTS scores to [0, 1] (divide by highest score)
  2. Vector scores already in [0, 1] (cosine similarity)
  3. Combined score: vec_score * 0.7 + fts_score * 0.3 for chunks found by both
  4. When only one channel returns results, its weight auto-adjusts to 1.0
  5. Per-user results receive a 1.2x boost
  6. Deduplication: if a chunk exists in both global and per-user scope, the per-user version wins

Fallback

When FTS returns no results (e.g., cross-language queries), a likeSearch() fallback runs ILIKE queries using up to 5 keywords (minimum 3 characters each), scoped to the agent's index.

Search Implementation

Aspect Detail
FTS engine PostgreSQL tsvector
Vector pgvector extension
Search function plainto_tsquery('simple', ...)
Distance operator <=> (cosine)

7. Context Files Routing

Context files are stored in two tables and routed based on agent type.

Tables

Table Scope Unique Key
agent_context_files Agent-level (agent_id, file_name)
user_context_files Per-user (agent_id, user_id, file_name)

Routing by Agent Type

Agent Type Agent-Level Files Per-User Files
open Template fallback only All files (SOUL, IDENTITY, AGENTS, TOOLS, BOOTSTRAP, USER)
predefined Agent-level files (SOUL, IDENTITY, AGENTS, TOOLS, BOOTSTRAP) Only USER.md

The ContextFileInterceptor checks agent type from context and routes read/write operations accordingly. For open agents, per-user files take priority with agent-level as fallback.


8. MCP Server Store

The MCP server store manages external tool server configurations and access grants.

Tables

Table Purpose
mcp_servers Server configurations (name, transport, command/URL, encrypted API key)
mcp_agent_grants Per-agent access grants with tool allow/deny lists
mcp_user_grants Per-user access grants with tool allow/deny lists
mcp_access_requests Pending/approved/rejected access requests

Transport Types

Transport Fields Used
stdio command, args (JSONB), env (JSONB)
sse url, headers (JSONB)
streamable-http url, headers (JSONB)

ListAccessible(agentID, userID) returns all MCP servers the given agent+user combination can access, with effective tool allow/deny lists merged from both agent and user grants.


9. Custom Tool Store

Dynamic tool definitions stored in PostgreSQL. Each tool defines a shell command template that the LLM can invoke at runtime.

Table: custom_tools

Column Type Description
id UUID v7 Primary key
name VARCHAR Unique tool name
description TEXT Tool description for the LLM
parameters JSONB JSON Schema for tool arguments
command TEXT Shell command template with {{.key}} placeholders
working_dir VARCHAR Optional working directory
timeout_seconds INT Execution timeout (default 60)
env BYTEA Encrypted environment variables (AES-256-GCM)
agent_id UUID NULL = global tool, UUID = per-agent tool
enabled BOOLEAN Soft enable/disable
created_by VARCHAR Audit trail

Scoping: Global tools (agent_id IS NULL) are loaded at startup into the global registry. Per-agent tools are loaded on-demand when the agent is resolved, using a cloned registry to avoid polluting the global one.


10. Delegation History

Table: delegation_history

Column Type Description
id UUID v7 Primary key
source_agent_id UUID Delegating agent
target_agent_id UUID Target agent
team_id UUID Team context (nullable)
team_task_id UUID Related team task (nullable)
user_id VARCHAR User who triggered the delegation
task TEXT Task description sent to target
mode VARCHAR(10) sync or async
status VARCHAR(20) completed, failed, cancelled
result TEXT Target agent's response
error TEXT Error message on failure
iterations INT Number of LLM iterations
trace_id UUID Linked trace for observability
duration_ms INT Wall-clock duration
completed_at TIMESTAMPTZ Completion timestamp

Every sync and async delegation is persisted here automatically via SaveDelegationHistory(). Results are truncated for WS transport (500 runes for list, 8000 runes for detail).


11. Team Store

The team store manages collaborative multi-agent teams with a shared task board and peer-to-peer mailbox.

Tables

Table Purpose Key Columns
agent_teams Team definitions name, lead_agent_id (FK → agents), status, settings (JSONB)
agent_team_members Team membership PK (team_id, agent_id), role (lead/member)
team_tasks Shared task board subject, status (pending/in_progress/completed/blocked), owner_agent_id, blocked_by (UUID[]), priority, result, tsv (FTS)
team_messages Peer-to-peer mailbox from_agent_id, to_agent_id (NULL = broadcast), content, message_type (chat/broadcast), read

TeamStore Interface (22 methods)

Team CRUD: CreateTeam, GetTeam, DeleteTeam, ListTeams

Members: AddMember, RemoveMember, ListMembers, GetTeamForAgent (find team by agent)

Tasks: CreateTask, UpdateTask, ListTasks (orderBy: priority/newest, statusFilter: active/completed/all), GetTask, SearchTasks (FTS on subject+description), ClaimTask, CompleteTask

Delegation History: SaveDelegationHistory, ListDelegationHistory (with filter opts), GetDelegationHistory

Messages: SendMessage, GetUnread, MarkRead

Atomic Task Claiming

Two agents grabbing the same task is prevented at the database level:

UPDATE team_tasks
SET status = 'in_progress', owner_agent_id = $1
WHERE id = $2 AND status = 'pending' AND owner_agent_id IS NULL

One row updated = claimed. Zero rows = someone else got it. Row-level locking, no distributed mutex needed.

Task Dependencies

Tasks can declare blocked_by (UUID array) pointing to prerequisite tasks. When a task is completed via CompleteTask, all dependent tasks whose blockers are now all completed are automatically unblocked (status transitions from blocked to pending).


12. Additional Store Interfaces

BuiltinToolStore

System tool metadata storage. Built-in tools are seeded at startup with category, settings, and dependency metadata. Only enabled and settings are user-editable.

Method Purpose
List() Return all tool definitions
Get(name) Fetch tool by name
Update(name, updates) Modify settings or enabled status
Seed(tools) Populate tools at startup
ListEnabled() Return only enabled tools
GetSettings(name) Fetch settings JSON for a tool

PendingMessageStore

Offline message queue for group chats. Buffers messages when the bot is not actively listening, auto-compacts into summaries to prevent unbounded growth.

Method Purpose
AppendBatch(msgs) Insert multiple messages in one query
ListByKey(channelName, historyKey) Retrieve buffered messages for a group
DeleteByKey(channelName, historyKey) Clear messages after processing
Compact(deleteIDs, summary) Atomically delete old messages + insert summary
DeleteStale(olderThan) Prune messages older than duration
ListGroups() Return distinct channel+key groups with counts
CountAll() Total pending messages across all groups
ResolveGroupTitles(groups) Look up chat titles from session metadata

KnowledgeGraphStore

Entity-relationship graph storage for AI inference and knowledge extraction. Supports graph traversal, confidence pruning, and bulk ingestion.

Method Purpose
UpsertEntity(entity) Create or update entity node
GetEntity(agentID, userID, entityID) Fetch single entity
DeleteEntity(agentID, userID, entityID) Remove entity (cascades relations)
ListEntities(agentID, userID, opts) List with pagination and type filter
SearchEntities(agentID, userID, query, limit) Full-text search entities
UpsertRelation(relation) Create or update edge
DeleteRelation(agentID, userID, relationID) Remove edge
ListRelations(agentID, userID, entityID) Get edges connected to an entity
Traverse(agentID, userID, startEntityID, maxDepth) Breadth-first graph traversal
IngestExtraction(agentID, userID, entities, relations) Bulk insert from LLM extraction
PruneByConfidence(agentID, userID, minConfidence) Remove low-confidence nodes/edges
Stats(agentID, userID) Aggregate entity and relation counts

ContactStore

Auto-collected channel contact registry. Tracks users across platforms and supports cross-channel deduplication (merge contacts as same person).

Method Purpose
UpsertContact(...) Create or update contact; on conflict (channel_type, sender_id) updates metadata
ListContacts(opts) Search with pagination and filters (ILIKE on name/username/sender_id)
CountContacts(opts) Count matching contacts
GetContactsBySenderIDs(senderIDs) Batch lookup contacts by sender IDs
MergeContacts(contactIDs) Link multiple contacts as same person (set merged_id)

ActivityStore

Audit logging for compliance and troubleshooting. Logs all significant actions with actor, entity, and optional details.

Method Purpose
Log(entry) Record a single audit entry
List(opts) Retrieve audit logs with filters (actor_type, action, entity_type, etc.)
Count(opts) Count matching audit entries

SnapshotStore

Pre-computed usage snapshots (hourly aggregations) for analytics dashboards. Tracks token usage, cost, request counts, and tool utilization.

Method Purpose
UpsertSnapshots(snapshots) Insert or replace batch of hourly aggregations
GetTimeSeries(query) Fetch hourly or daily time series for charting
GetBreakdown(query) Aggregate by dimension (provider, model, channel, agent)
GetLatestBucket() Return most recent bucket_hour (worker resume point)

SecureCLIStore

CLI binary credential configuration with encrypted environment variable injection. Credentials are auto-injected into child processes without exposing them to command output.

Method Purpose
Create(binary) Register new CLI binary config
Get(id) Fetch config by ID
Update(id, updates) Modify settings (enable/disable, denyArgs, etc.)
Delete(id) Remove config
List() Return all configs
ListByAgent(agentID) Return configs for a specific agent
LookupByBinary(binaryName, agentID) Find best-matching config (agent-specific > global)
ListEnabled() Return enabled configs for TOOLS.md generation

APIKeyStore

Gateway API key management. Keys are SHA-256 hashed at rest; validation compares hash to incoming key. Supports scopes, expiration, and revocation.

Method Purpose
Create(key) Insert new API key record
GetByHash(keyHash) Lookup active (non-revoked, non-expired) key by hash
List() Return all keys for admin display (hashes omitted)
Revoke(id) Mark key as revoked
Delete(id) Permanently remove key
TouchLastUsed(id) Update last_used_at timestamp

14. Database Schema

All tables use UUID v7 (time-ordered) as primary keys via GenNewID().

flowchart TD
    subgraph Providers
        LP["llm_providers"] --> LM["llm_models"]
    end

    subgraph Agents
        AG["agents"] --> AS["agent_shares"]
        AG --> ACF["agent_context_files"]
        AG --> UCF["user_context_files"]
        AG --> UAP["user_agent_profiles"]
    end

    subgraph Teams
        AT["agent_teams"] --> ATM["agent_team_members"]
        AT --> TT["team_tasks"]
        AT --> TM["team_messages"]
    end

    subgraph Sessions
        SE["sessions"]
    end

    subgraph Memory
        MD["memory_documents"] --> MC["memory_chunks"]
    end

    subgraph Cron
        CJ["cron_jobs"] --> CRL["cron_run_logs"]
    end

    subgraph Pairing
        PR["pairing_requests"]
        PD["paired_devices"]
    end

    subgraph Skills
        SK["skills"] --> SAG["skill_agent_grants"]
        SK --> SUG["skill_user_grants"]
    end

    subgraph Tracing
        TR["traces"] --> SP["spans"]
    end

    subgraph MCP
        MS["mcp_servers"] --> MAG["mcp_agent_grants"]
        MS --> MUG["mcp_user_grants"]
        MS --> MAR["mcp_access_requests"]
    end

    subgraph "Custom Tools"
        CT["custom_tools"]
    end

Key Tables

Table Purpose Key Columns
agents Agent definitions agent_key (UNIQUE), owner_id, agent_type (open/predefined), is_default, frontmatter, tsv, embedding, soft delete via deleted_at
agent_shares Agent RBAC sharing UNIQUE(agent_id, user_id), role (user/admin/operator)
agent_context_files Agent-level context UNIQUE(agent_id, file_name)
user_context_files Per-user context UNIQUE(agent_id, user_id, file_name)
user_agent_profiles User tracking first_seen_at, last_seen_at, workspace
agent_teams Team definitions name, lead_agent_id, status, settings (JSONB)
agent_team_members Team membership PK(team_id, agent_id), role (lead/member)
team_tasks Shared task board subject, status, owner_agent_id, blocked_by (UUID[]), tsv (FTS)
team_messages Peer-to-peer mailbox from_agent_id, to_agent_id, message_type, read
delegation_history Persisted delegation records source_agent_id, target_agent_id, mode, status, result, trace_id
sessions Conversation history session_key (UNIQUE), messages (JSONB), summary, token counts
memory_documents Memory docs UNIQUE(agent_id, COALESCE(user_id, ''), path)
memory_chunks Chunked + embedded text embedding (VECTOR), tsv (TSVECTOR)
llm_providers Provider configuration api_key (AES-256-GCM encrypted)
traces LLM call traces agent_id, user_id, status, parent_trace_id, aggregated token counts
spans Individual operations span_type (llm_call, tool_call, agent, embedding), parent_span_id
skills Skill definitions Content, metadata, grants
cron_jobs Scheduled tasks schedule_kind (at/every/cron), payload (JSONB)
mcp_servers MCP server configs transport, api_key (encrypted), tool_prefix
custom_tools Dynamic tool definitions command (template), agent_id (NULL = global), env (encrypted)

Migrations

Migration Purpose
000001_init_schema Core tables (agents, sessions, providers, memory, cron, pairing, skills, traces, MCP, custom tools)
000002_agent_links agent_links table + frontmatter, tsv, embedding on agents + parent_trace_id on traces
000003_agent_teams agent_teams, agent_team_members, team_tasks, team_messages + team_id on agent_links
000004_teams_v2 FTS on team_tasks (tsv column) + delegation_history table
000005_phase4 Additional team and delegation features

Required PostgreSQL Extensions

  • pgvector: Vector similarity search for memory embeddings
  • pgcrypto: UUID generation functions

15. Context Propagation

Metadata flows through context.Context instead of mutable state, ensuring thread safety across concurrent agent runs.

flowchart TD
    HANDLER["HTTP/WS Handler"] -->|"store.WithUserID(ctx)<br/>store.WithAgentID(ctx)<br/>store.WithAgentType(ctx)"| LOOP["Agent Loop"]
    LOOP -->|"tools.WithToolChannel(ctx)<br/>tools.WithToolChatID(ctx)<br/>tools.WithToolPeerKind(ctx)"| TOOL["Tool Execute(ctx)"]
    TOOL -->|"store.UserIDFromContext(ctx)<br/>store.AgentIDFromContext(ctx)<br/>tools.ToolChannelFromCtx(ctx)"| LOGIC["Domain Logic"]

Store Context Keys

Key Type Purpose
goclaw_user_id string External user ID (e.g., Telegram user ID)
goclaw_agent_id uuid.UUID Agent UUID
goclaw_agent_type string Agent type: "open" or "predefined"
goclaw_sender_id string Original individual sender ID (in group chats, user_id is group-scoped but sender_id preserves the actual person)

Tool Context Keys

Key Purpose
tool_channel Current channel (telegram, discord, etc.)
tool_chat_id Chat/conversation identifier
tool_peer_kind Peer type: "direct" or "group"
tool_sandbox_key Docker sandbox scope key
tool_async_cb Callback for async tool execution
tool_workspace Per-user workspace directory (injected by agent loop, read by filesystem/shell tools)

16. Key PostgreSQL Patterns

Database Driver

All PG stores use database/sql with the pgx/v5/stdlib driver. No ORM is used -- all queries are raw SQL with positional parameters ($1, $2, ...).

Nullable Columns

Nullable columns are handled via Go pointers: *string, *int, *time.Time, *uuid.UUID. Helper functions nilStr(), nilInt(), nilUUID(), nilTime() convert zero values to nil for clean SQL insertion.

Dynamic Updates

execMapUpdate() builds UPDATE statements dynamically from a map[string]any of column-value pairs. This avoids writing a separate UPDATE query for every combination of updatable fields.

Upsert Pattern

All "create or update" operations use INSERT ... ON CONFLICT DO UPDATE, ensuring idempotency:

Operation Conflict Key
SetAgentContextFile (agent_id, file_name)
SetUserContextFile (agent_id, user_id, file_name)
ShareAgent (agent_id, user_id)
PutDocument (memory) (agent_id, COALESCE(user_id, ''), path)
GrantToAgent (skill) (skill_id, agent_id)

User Profile Detection

GetOrCreateUserProfile uses the PostgreSQL xmax trick:

  • xmax = 0 after RETURNING means a real INSERT occurred (new user) -- triggers context file seeding
  • xmax != 0 means an UPDATE on conflict (existing user) -- no seeding needed

Batch Span Insert

BatchCreateSpans inserts spans in batches of 100. If a batch fails, it falls back to inserting each span individually to prevent data loss.


17. File Reference

File Purpose
internal/store/stores.go Stores container struct (all 22 store interfaces)
internal/store/types.go BaseModel, StoreConfig, GenNewID()
internal/store/context.go Context propagation: WithUserID, WithAgentID, WithAgentType, WithSenderID
internal/store/session_store.go SessionStore interface, SessionData, SessionInfo
internal/store/memory_store.go MemoryStore interface, MemorySearchResult, EmbeddingProvider
internal/store/skill_store.go SkillStore interface
internal/store/agent_store.go AgentStore interface
internal/store/team_store.go TeamStore interface, TeamData, TeamTaskData, DelegationHistoryData, TeamMessageData
internal/store/provider_store.go ProviderStore interface
internal/store/tracing_store.go TracingStore interface, TraceData, SpanData
internal/store/mcp_store.go MCPServerStore interface, grant types, access request types
internal/store/channel_instance_store.go ChannelInstanceStore interface
internal/store/config_secrets_store.go ConfigSecretsStore interface
internal/store/pairing_store.go PairingStore interface
internal/store/cron_store.go CronStore interface
internal/store/custom_tool_store.go CustomToolStore interface
internal/store/builtin_tool_store.go BuiltinToolStore interface, system tool metadata
internal/store/pending_message_store.go PendingMessageStore interface, group message queue
internal/store/knowledge_graph_store.go KnowledgeGraphStore interface, entities and relations
internal/store/contact_store.go ContactStore interface, channel contact tracking
internal/store/activity_store.go ActivityStore interface, audit logs
internal/store/snapshot_store.go SnapshotStore interface, usage aggregation
internal/store/secure_cli_store.go SecureCLIStore interface, CLI credential injection
internal/store/api_key_store.go APIKeyStore interface, gateway API keys
internal/store/pg/factory.go PG store factory: creates all PG store instances from a connection pool
internal/store/pg/sessions.go PGSessionStore: session cache, Save, GetOrCreate
internal/store/pg/agents.go PGAgentStore: CRUD, soft delete, access control
internal/store/pg/agents_context.go Agent and user context file operations
internal/store/pg/teams.go PGTeamStore: teams, tasks (atomic claim), messages, delegation history
internal/store/pg/memory_docs.go PGMemoryStore: document CRUD, indexing, chunking
internal/store/pg/memory_search.go Hybrid search: FTS, vector, ILIKE fallback, merge
internal/store/pg/skills.go PGSkillStore: skill CRUD and grants
internal/store/pg/skills_grants.go Skill agent and user grants
internal/store/pg/mcp_servers.go PGMCPServerStore: server CRUD, grants, access requests
internal/store/pg/channel_instances.go PGChannelInstanceStore: channel instance CRUD
internal/store/pg/config_secrets.go PGConfigSecretsStore: encrypted config secrets
internal/store/pg/custom_tools.go PGCustomToolStore: custom tool CRUD with encrypted env
internal/store/pg/providers.go PGProviderStore: provider CRUD with encrypted keys
internal/store/pg/tracing.go PGTracingStore: traces and spans with batch insert
internal/store/pg/pool.go Connection pool management
internal/store/pg/helpers.go Nullable helpers, JSON helpers, execMapUpdate()
internal/store/validate.go Input validation utilities
internal/tools/context_keys.go Tool context keys including WithToolWorkspace