Assess UAE cybersecurity regulatory compliance (NESA IAS, Dubai ISR, CBUAE, TDRA). Returns applicable framework, compliance score, critical gaps, and mandatory controls.
| Name | Required | Description | Default |
|---|---|---|---|
| emirate | Yes | dubai, abu_dhabi, sharjah, federal, other | |
| has_isms | Yes | ||
| is_cloud_hosted | Yes | ||
| organisation_type | Yes | ||
| has_incident_response | Yes | ||
| has_third_party_audit | Yes | ||
| has_data_classification | Yes | ||
| has_vulnerability_assessment | 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 present, the description carries the disclosure burden. It explicitly states the assessment nature and the exact outputs: applicable framework, compliance score, critical gaps, and mandatory controls. This implies a non-mutating calculation, though it does not discuss edge cases or data handling.
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 that packs in the domain, the relevant frameworks, and the output contract. There is no filler or tautological restatement of the tool name.
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?
For an 8-parameter tool with no output schema and no annotations, the description covers return values but omits how the inputs influence framework selection and what exclusions apply relative to other compliance checks. It is concise but leaves the agent to infer part of the decision logic.
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 only 13%, and the description does not compensate for this gap. It does not explain how organisation_type, emirate, or the boolean control flags map to the listed frameworks. The parameter names are somewhat self-evident, but the description adds little meaning beyond the raw schema.
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 uses a specific verb ('Assess') and a specific resource ('UAE cybersecurity regulatory compliance'), and it names distinct frameworks (NESA IAS, Dubai ISR, CBUAE, TDRA). This clearly distinguishes it from sibling tools like check_nis2_readiness and check_uae_bim_compliance, and the return contents are also stated.
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 description provides clear context: use this tool when dealing with UAE cybersecurity regulatory compliance under NESA IAS, Dubai ISR, CBUAE, or TDRA. It does not explicitly list exclusions or alternatives, but the context is specific enough for an agent to route to this tool correctly.
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.
Many tools have distinct domains (structural, carbon, compliance, heat pumps), but several overlap at a surface level: calculate_carbon, building_carbon_footprint, and uae_climate_ghg all deal with carbon; estimate_cooling_load and thermal_load both compute cooling loads; and multiple UK/UAE compliance checkers have similar 'readiness/checker/precheck' names. Descriptions help differentiate, but an agent could still select the wrong tool without careful reading.
Naming is a mix of verb-led patterns (assess_epbd_score, calculate_carbon, check_uae_bim_compliance, estimate_cooling_load, get_technical_dd_quote) and noun-led phrases (building_carbon_footprint, building_readiness, digital_renovation_passport, roi_calculator, thermal_load). Sub-groups like check_* and eurocode_* are consistent internally, but the overall set has no unifying convention, which adds cognitive load.
With 27 tools, the server exceeds the 'heavy' range, even though the engineering domain is broad. Many tools are highly specialized (e.g., part_s_ev, mees_checker, dgnb_bim_readiness), and the large count risks overwhelming an agent trying to pick the right one. The scope may justify the number, but it edges into too-many territory.
The server covers a wide range of building and sustainability assessments: carbon, energy, compliance (EU/UK/UAE), structural design, cost benchmarking, and data centres. However, there are gaps in adjacent areas common to building engineering—such as acoustic design, water/sanitation, electrical systems, or thermal bridging—which would be expected from a general 'engineering' server. It is reasonably complete for its apparent sustainability/regulatory focus, but not universally.
