Create a dependency link between two entities.
| Name | Required | Description | Default |
|---|---|---|---|
| notes | No | ||
| to_id | Yes | Entity depended upon | |
| from_id | Yes | Entity that depends | |
| to_name | No | ||
| from_name | No | ||
| criticality | No | ||
| dependency_type | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only says 'Create', which implies mutation, but does not mention idempotency, overwrite behavior, validation of entity existence, or side effects. This is insufficient for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise, but it is under-specified. It lacks essential details, making it an example of under-specification rather than effective conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 7 parameters, 2 enums, and no output schema, yet the description provides almost no context. It does not explain return values, error conditions, or any required dependencies or prerequisites. The description is inadequate for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is low (29%: only to_id and from_id have descriptions). The description does not compensate by explaining any parameters. It does not mention criticality, dependency_type, notes, or names, leaving the agent with limited semantic understanding beyond property names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create') and the resource ('a dependency link between two entities'). It distinguishes from read-only tools like dependency_graph by implying a write operation, though it does not explicitly contrast with siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description simply states what it does, with no context about scenarios, prerequisites, or exclusions. This qualifies as 'no guidance' rather than misleading.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool serves a distinct purpose: inventory, registration, dependency mapping, graph retrieval, and various analyses. While blast_radius and impact_simulation are related, their descriptions clearly differentiate static impact calculation from cascade simulation.
All names use snake_case, but there is a mix of noun phrases (asset_inventory, blast_radius) and verb phrases (map_dependency, register_asset). This inconsistency in part-of-speech reduces predictability, though still readable and understandable.
Ten tools is well-scoped for an ICT dependency analysis platform. Each tool covers a meaningful operation without redundancy or bloat.
The set covers creation, reading, and analysis well, but it lacks update and delete operations for assets, dependencies, and functions. This leaves lifecycle management incomplete, forcing agents to work around missing mutations.