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Glama

generate_scenarios

List all 8 TIBER-EU scenarios available for autonomous simulation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

The description discloses that the tool lists scenarios, implying a read-only operation with no side effects. However, since no annotations are provided, the description carries the full burden for behavioral disclosure, and it does not explicitly state that it is non-destructive or that it does not trigger simulations. For a simple list operation, this level of disclosure appears adequate.

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?

The description is a single, front-loaded sentence that gets straight to the point. Every word earns its place, with no fluff or repetition.

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?

The description tells the agent exactly what output to expect (a list of 8 scenarios) and the domain (TIBER-EU), which is sufficient for a parameterless tool. However, it does not specify the output format or whether the scenarios are returned as names, IDs, or objects.

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?

The tool has zero parameters, so the schema fully covers param semantics. The description adds contextual value by noting the scenarios are for autonomous simulation, but no parameter documentation is needed.

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 uses the specific verb 'List' and identifies the resource 'all 8 TIBER-EU scenarios available for autonomous simulation.' It clearly distinguishes the tool from siblings like 'auto_simulate' by positioning it as a listing operation. The clarity is slightly undermined by the tool name suggesting generation, but the description itself is unambiguous.

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?

No guidance is provided on when to use this tool versus alternatives. It does not mention any prerequisites, exclusions, or related tools. An agent would not know if this should be called before simulation or in place of another listing tool.

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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TDQS

C2.8/5.0
Disambiguation4/5

Most tools have distinct purposes, but potential confusion exists between 'auto_simulate' and 'generate_scenarios' (both involve scenario generation) and between 'health_check' and 'ping' (both test connectivity). Descriptions help mitigate but do not eliminate ambiguity.

Naming Consistency3/5

Tool names consistently use snake_case but mix verb-based (generate_scenarios, register_exercise) and noun-based (evidence_bundle, threat_profile) patterns. 'ping' is a single word, breaking the pattern. This inconsistency may confuse agents about whether a tool performs an action or represents a resource.

Tool Count5/5

17 tools cover the breadth of TLPT activities (scoping, simulation, findings, compliance) without being overwhelming. Each tool serves a distinct part of the workflow, making the count well-scoped for domain complexity.

Completeness4/5

The tool set covers major TLPT lifecycle phases: preparation (threat_profile), scenario generation (generate_scenarios, auto_simulate), execution mapping (attack_chain, mitre_map), findings (finding_register, remediation_plan), compliance (obligation_map, sync_to_ampel), and scheduling (test_calendar). Minor gaps like a dedicated reporting tool exist but can be worked around.

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