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gitmem-dev

GitMem

Official
by gitmem-dev

graph_traverse

Traverse the knowledge graph of institutional memory with four lenses: connected_to, produced_by, provenance, and stats. Trace decisions, find what an agent produced, or get aggregate counts.

Instructions

Traverse the knowledge graph over institutional memory triples. Answers: 'show me everything connected to this issue', 'what did this agent produce', 'trace this decision back', 'which issues produced the most learnings'. Four lenses: connected_to, produced_by, provenance, stats.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lensYesTraversal mode: connected_to (all connections to a node), produced_by (what an agent/persona produced), provenance (trace origin chain), stats (aggregate counts)
nodeNoStarting node. Examples: 'PROJ-123', 'cli', 'Scar: Done ≠ Deployed'. Required for all lenses except stats.
depthNoMax chain depth for provenance lens (default: 3)
limitNoMax triples to return (default: 50)
projectNoProject namespace (e.g., 'my-project'). Scopes sessions and searches.
predicateNoFilter by predicate (optional)
Behavior2/5

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

No annotations provided. Description implies a read-only operation but does not explicitly state safety, idempotency, or any side effects. This is a minimal disclosure.

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?

Two concise sentences plus a list of lenses. Every sentence is informative and front-loaded. No wasted words.

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

Completeness4/5

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

Covers the main use cases and output type (triples). Could mention depth/limit defaults, but those are in the schema. Adequate for a query tool without output schema.

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

Parameters5/5

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

All 6 parameters are described in the schema, and the description adds context by linking lenses to example questions and providing example node values. This goes beyond the schema definitions.

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?

Description clearly states it traverses a knowledge graph, provides example queries, and lists four traversal lenses. This distinguishes it from sibling tools like search or recall.

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

Usage Guidelines3/5

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

Example questions imply when to use the tool (e.g., 'show me everything connected'), but no explicit guidance on when not to use it or comparison with alternatives like analyze or search.

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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