Agentdb QueryCAUTION
🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated
Overview
🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated
ef7d4f0535e5OBSERVED · 2026-09-25What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
--- name: agentdb-query description: Query AgentDB through the controller bridge -- semantic routing, hierarchical recall, causal graphs, context synthesis, pattern store/search argument-hint: "<query>" allowed-tools: mcp__plugin_ruflo-core_ruflo__agentdb_semantic-route mcp__plugin_ruflo-core_ruflo__agentdb_hierarchical-recall mcp__plugin_ruflo-core_ruflo__agentdb_hierarchical-store mcp__plugin_ruflo-core_ruflo__agentdb_context-synthesize mcp__plugin_ruflo-core_ruflo__agentdb_causal-edge mcp__plugin_ruflo-core_ruflo__agentdb_pattern-search mcp__plugin_ruflo-core_ruflo__agentdb_pattern-store mcp__plugin_ruflo-core_ruflo__agentdb_controllers mcp__plugin_ruflo-core_ruflo__agentdb_health mcp__plugin_ruflo-core_ruflo__agentdb_batch mcp__plugin_ruflo-core_ruflo__agentdb_feedback mcp__plugin_ruflo-core_ruflo__agentdb_consolidate mcp__plugin_ruflo-core_ruflo__agentdb_session-start mcp__plugin_ruflo-core_ruflo__agentdb_session-end Bash --- # AgentDB Query Query and manage AgentDB through the controller bridge. AgentDB exposes 15 `agentdb_*` MCP tools; this skill enumerates the standard usage path. ## When to use When you need to store, retrieve, or search knowledge across agent sessions. AgentDB provides hierarchical storage, causal knowledge graphs, semantic routing, and context synthesis. ## Steps 1. **Check health** — `mcp__plugin_ruflo-core_ruflo__agentdb_health`. Sanity-check `available: true`. 2. **Start session** — `mcp__plugin_ruflo-core_ruflo__agentdb_session-start` if not already active. 3. **Store knowledge** — `mcp__plugin_ruflo-core_ruflo__agentdb_hierarchical-store` for structured tier-keyed data (tiers: `working|episodic|semantic`). 4. **Recall knowledge** — `mcp__plugin_ruflo-core_ruflo__agentdb_hierarchical-recall` with a query. 5. **Search patterns** — `mcp__plugin_ruflo-core_ruflo__agentdb_pattern-search` for learned patterns (ReasoningBank-routed). 6. **Synthesize context** — `mcp__plugin_ruflo-core_ruflo__agentdb_context-synthesize` to combine multiple memories. 7. **Build causal graph** — `mcp__plugin_ruflo-core_ruflo__agentdb_causal-edge` to link related knowledge. ## Available controller groups Call `mcp__plugin_ruflo-core_ruflo__agentdb_controllers` to list the runtime registry. Functional categories surfaced via the 15 MCP tools: - **Hierarchical** — `agentdb_hierarchical-store`, `_recall` (tier-routed) - **Pattern** — `agentdb_pattern-store`, `_search` (ReasoningBank-routed) - **Semantic** — `agentdb_semantic-route`, `_context-synthesize` - **Causal** — `agentdb_causal-edge` (graph-node backend with bridge fallback) - **Lifecycle** — `agentdb_health`, `_controllers`, `_session-start`, `_session-end` - **Bulk** — `agentdb_batch` (≤500 entries), `_consolidate` - **Quality** — `agentdb_feedback` ## Important: namespace handling Namespace strings apply to `memory_*` and `embeddings_search` only. The `agentdb_hierarchical-*`, `agentdb_pattern-*`, and `agentdb_causal-edge` tools route by **tier** or **controller**, not namespace. Don't pass `namespace: 'foo'` to those tools — it will be silently ignored. See plugin README "Namespace convention". ## Operational fallbacks (branch on these) - `controller: 'memory-store-fallback'` — pattern persisted via `memory_store --namespace pattern`. NOT a failure. - `_graphNodeBackend: true` — causal-edge handled by `@ruvector/graph-node`. - `success: false, error: '...Use memory_store/memory_search instead.'` — bridge unavailable; switch to `memory_*` tools per the README replacement table. ## CLI alternative ```bash npx @claude-flow/cli@latest memory search --query "your query" --namespace patterns npx @claude-flow/cli@latest memory store --key "key" --value "value" --namespace patterns npx @claude-flow/cli@latest memory list --namespace patterns ```
Trust audit
CAUTIONgrade B · trust 89/100 Install with care. The audit found things worth knowing before you trust its output.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | WARN |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (4)
crates
plugin/agents
plugin/commands
plugin/skills
Gates applied: no_behavioural_pass.
ef7d4f0535e5full audit observations/trust-audit/skill/ruvnet__agentdb-query.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-09-25 | ef7d4f0535e5 | CAUTION | B | 89 | first audit |
Questions
What does the Agentdb Query skill do?
🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated
Is Agentdb Query safe to install?
With care. The audit graded it B (89/100) and found 4 things worth knowing before you trust this skill, listed below with the exact line each was found on.
What can Agentdb Query access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (ef7d4f0535e5), read on 2026-09-25. The repository is watched, and a new audit runs when it changes — this is the first audit.