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Glama

find_path

Find the shortest connection path between two journal captures by analyzing references, shared entities, relations, and tag overlap.

Instructions

Find the shortest chain of connections between two captures — how one
idea reaches another through references, shared entities, asserted
relations, and strong tag overlap.

Args:
    from_id: Starting capture (numeric ID).
    to_id:   Destination capture (numeric ID).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
to_idYes
from_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv3.9.0

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does add real behavioral context by enumerating how two captures can be linked (references, shared entities, asserted relations, tag overlap), which is more than the schema conveys. However, it says nothing about read-only nature, cost/latency of a graph search, what happens when no path exists, or path optimality guarantees.

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

Conciseness4/5

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

The core purpose is front-loaded in the first sentence with the edge-type detail immediately after, and the Args block is minimal. The args section largely restates the schema, but the 'numeric ID' clarification earns its place.

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

Completeness3/5

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

An output schema exists, so return-value explanation is not required. The description is adequate for a two-parameter read tool, but gaps remain: no sibling differentiation for a crowded graph-query namespace, no no-path/error behavior, and no indication of search direction or scope.

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?

Schema description coverage is 0%, so the description must compensate, and it does document both parameters with meaning: from_id as the starting capture and to_id as the destination, both numeric IDs. Type and directionality are clear, though no constraints (e.g., valid ID range, self-path handling) are given.

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

Purpose4/5

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

The description gives a specific verb and resource ('find the shortest chain of connections between two captures') and even names the edge types traversed (references, shared entities, asserted relations, tag overlap). It does not, however, distinguish itself from close siblings like find_connections, surface_connections, or neighborhood, which an agent could easily confuse it with.

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

Usage Guidelines2/5

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

There is no explicit when-to-use guidance, no conditions under which this is preferred over alternatives, and no mention of the many graph-related siblings (find_connections, surface_connections, neighborhood). The agent must infer usage purely from the purpose sentence.

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