blast_radius
Calculate blast radius — what breaks if this entity fails.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| entity_id | Yes |
Calculate blast radius — what breaks if this entity fails.
| Name | Required | Description | Default |
|---|---|---|---|
| entity_id | Yes |
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 provided, the description carries full responsibility for behavioral disclosure. It only states the calculation purpose and does not mention whether the operation is read-only, requires permissions, or has side effects. The behavior beyond the basic calculation is opaque.
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, front-loaded sentence with an clarifying em-dash clause. Every word earns its place, and there is no redundant information or filler.
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?
Given the lack of an output schema, annotations, and parameter documentation, the description should at least hint at the return value or behavior. It does not explain what 'blast radius' output looks like (e.g., list of affected entities) or any edge cases, leaving the agent with insufficient context for correct invocation and result interpretation.
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?
The schema provides no description for entity_id (0% coverage), and the tool description does not elaborate on what an 'entity' is or what format that ID should take. The description only rephrases the parameter's existence, adding minimal semantic value.
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 tool calculates blast radius and defines it as 'what breaks if this entity fails.' This is a specific verb+resource pair that distinguishes it from sibling tools like criticality_score or dependency_graph.
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?
The usage is implied by the description: one would use this tool when needing to know what breaks if an entity fails. However, there is no explicit guidance on when to use this tool over siblings like impact_simulation or spof_analysis, nor any exclusion criteria.
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.