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VelixarAi

Velixar MCP Server

Official
by VelixarAi

velixar_lineage

Walk the derivation lineage of a memory to see its ancestors and descendants in the knowledge graph, revealing the chain of reasoning from origins to derived insights.

Instructions

Trace the DERIVATION lineage of a memory — the knowledge-building graph, NOT similarity. Every edge was declared at store time via source_ids ("this memory was reasoned/built FROM those"). This answers "what understanding did this come from, and what was built on it" — fundamentally different from velixar_search_neighborhood, which finds memories that merely resemble one another in vector space. Upstream = ancestors (what it was built on); downstream = descendants (what was built on it). A memory with no ancestors is an origin (learned fresh). Returns nodes (each with hop distance and is_origin) and directed child→parent edges.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
depthNoHow many derivation hops to walk (default 3, max 6)
directionNoup = what this was built on (ancestors); down = what was built on this (descendants); both (default)
memory_idYesThe memory whose derivation lineage to trace
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It discloses that edges are declared at store time via source_ids, returns nodes with hop distance and is_origin, and directed child→parent edges. It implicitly indicates read-only behavior, though explicit statement of non-destructiveness would be ideal.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured, with the key distinction provided upfront. Every sentence adds value, no fluff or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description effectively explains the return format (nodes with hop distance and is_origin, directed edges) and the concept of origins. It provides sufficient context for an agent to understand what the tool does and what to expect.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All 3 parameters are fully described in the schema (100% coverage). The description adds value by providing context for the direction parameter (explaining 'up' vs 'down' in terms of ancestors/descendants) and clarifying the meaning of depth. This goes beyond the schema's short descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool traces derivation lineage (knowledge-building graph) and explicitly distinguishes it from similarity search (velixar_search_neighborhood). It uses specific verbs ('Trace the DERIVATION lineage') and defines key concepts (ancestors, descendants, origins).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit when-to-use guidance (understanding what a memory was built from and what was built on it) and when-not-to-use (not for similarity, which belongs to velixar_search_neighborhood). It also explains the meaning of direction parameters (up=ancestors, down=descendants).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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