agentdb-query

AI Community

Repo stars 54,444
Author repo ruflo

Interpretation is structured for decision-making; original keeps the upstream SKILL.md unchanged.

Decide Fit First

Core job: Query AgentDB through the controller bridge -- semantic routing, hierarchical recall, causal graphs, context synthesis, pattern…
Best fit: Use it when the task has reusable inputs, steps, and validation criteria rather than a one-off answer.
Avoid forcing it: If the source lacks commands, platform support, or external-service evidence, keep those fields unknown instead of guessing.

Design Intent

Structure: The skill is organized around “When to use”, “Steps”, “Available controller groups”, “Important: namespace handling”, showing how the author expects the agent to judge fit, collect context, and produce verifiable output.
Trigger evidence: Prioritize the author’s wording around when to use it, what context to collect, and what output shape to produce.
Evidence boundary: Author text states facts, repository files prove commands and paths, and Fluxly only adds fit, limits, and usage judgment.

How To Use It

Inputs: Provide target material, scope, expected result, forbidden changes, and validation method.
Invocation: Name agentdb-query directly; if the source includes slash commands, start with the command and then add task context.
Validation: Start small and check whether the result follows “When to use / Steps / Available controller groups” before expanding.

Boundaries And Review

Dependencies: It usually needs no extra API key, so start with a small validation task.
Permissions: Declared permissions include read; ask the agent to state file, command, and rollback boundaries before acting.
Quality bar: A useful result names the deliverable, evidence, and next action. Generic prose means the task needs tighter context.

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

Check health — mcp__claude-flow__agentdb_health. Sanity-check available: true.
Start session — mcp__claude-flow__agentdb_session-start if not already active.
Store knowledge — mcp__claude-flow__agentdb_hierarchical-store for structured tier-keyed data (tiers: working|episodic|semantic).
Recall knowledge — mcp__claude-flow__agentdb_hierarchical-recall with a query.
Search patterns — mcp__claude-flow__agentdb_pattern-search for learned patterns (ReasoningBank-routed).
Synthesize context — mcp__claude-flow__agentdb_context-synthesize to combine multiple memories.
Build causal graph — mcp__claude-flow__agentdb_causal-edge to link related knowledge.

Available controller groups

Call mcp__claude-flow__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

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

Fluxly profile Author and license come from source; runtime, permissions, and network are Fluxly detections or estimates

Fluxly category: AI
Author-declared agents: No explicit declaration found; this is not inferred or tested compatibility
Static check: 88 / 100 · heuristic scan, not runtime safety proof
Author / version / license: @ruvnet · no license declared
Fluxly token estimate: Lean
Fluxly setup estimate: Plug-and-play
External API key: No requirement detected
Detected OS requirements: macOS · Linux · Windows
Runtime requirements: Node.js
Detected file/system behavior: Read-only
Detected network behavior: Local-only
Install commands: None (reference only)

Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.

Heads up: 未限定 allowed-tools，默认拥有全部工具权限。

Output preview agentdb-query.preview

The current SKILL.md does not define a fixed output example.

SKILL.md SKILL.md

# 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__claude-flow__agentdb_health`. Sanity-check `available: true`.
2. **Start session** — `mcp__claude-flow__agentdb_session-start` if not already active.
3. **Store knowledge** — `mcp__claude-flow__agentdb_hierarchical-store` for structured tier-keyed data (tiers: `working|episodic|semantic`).
4. **Recall knowledge** — `mcp__claude-flow__agentdb_hierarchical-recall` with a query.
5. **Search patterns** — `mcp__claude-flow__agentdb_pattern-search` for learned patterns (ReasoningBank-routed).
6. **Synthesize context** — `mcp__claude-flow__agentdb_context-synthesize` to combine multiple memories.
7. **Build causal graph** — `mcp__claude-flow__agentdb_causal-edge` to link related knowledge.

## Available controller groups

Call `mcp__claude-flow__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

…

Evidence boundary and execution chain

Author text anchors workflow facts; Fluxly only indexes current sections, terms, files, and commands.

sections -> When to use → Steps → Available controller groups → Important: namespace handling → Operational fallbacks (branch on these) → CLI alternative
terms    -> Check health · Start session · Store knowledge · Recall knowledge · Search patterns · Synthesize context · Build causal graph · Hierarchical
files/cmd -> agentdb · mcpclaude-flowagentdbhealth · available: true · mcpclaude-flowagentdbsession-start · mcpclaude-flowagentdbhierarchical-store · working|episodic|semantic · mcpclaude-flowagentdbhierarchical-recall · mcpclaude-flowagentdbpattern-search
body sha256 -> 72f5f3035f1f