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cache_related

Find connected cached entries by traversing similarity and derivation links from a known cache ID. Use this to retrieve related results already stored.

Instructions

Traverse the cache graph outward from one entry to find connected entries — ones auto-linked for content similarity ("similar" edges) or explicitly declared as built on top of it ("derived-from" edges). Use this to pull in everything already known that connects to a given cached result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesId of the entry to start from (from a prior cache_get/set/query result)
depthNoHops to traverse, default 1
limitNoMax results, default 20
relationNoFilter to one edge type

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.1

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden and does well: it explains that traversal is outward, that edges are auto-linked by similarity or explicitly declared as derived-from, and that the intent is to discover connected known entries. It does not dwell on destructive or permission implications, but traversal is clearly a read-oriented operation.

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 sentences, no filler. The core mechanism is front-loaded, and the usage guidance is delivered in the second sentence. Every word earns its place.

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?

For a graph traversal tool with no output schema and no annotations, the description is nearly sufficient: it explains what is traversed, the two edge types, and why you would use it. A fully complete description might also mention return shape or pagination behavior, but the schema's limit and depth parameters cover the main invocation concerns.

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

Parameters3/5

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

Schema coverage is 100%, so the baseline of 3 applies. The description reinforces the meaning of the relation enum by explaining both edge types, but it adds little beyond the schema for id, depth, and limit.

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 names the exact operation ('traverse the cache graph outward') and the resource ('one entry'), and distinguishes it from sibling CRUD/search tools by focusing on graph connectivity. It also names the two edge types, making the tool's function concrete and unambiguous.

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

Usage Guidelines4/5

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

The description gives a clear use case: pull in everything already known to connect to a cached result. It stops short of explicitly naming alternatives or saying when not to use it, but the graph-traversal framing effectively separates it from cache_get, cache_set, and cache_query.

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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