Building Readiness assessment for change-of-use / conversion. Returns a 0-100 readiness score, project complexity, four domain scores (structural, MEP, compliance, digital/BIM) with RAG, and recommendations.
| Name | Required | Description | Default |
|---|---|---|---|
| bim | Yes | ||
| floors | Yes | ||
| location | Yes | ||
| condition | Yes | ||
| structure | Yes | ||
| year_built | Yes | ||
| current_use | Yes | ||
| proposed_use | 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 the full burden of behavioral disclosure. It describes the output (score, complexity, domain scores, RAG, recommendations) but does not explicitly state whether the tool is read-only, what side effects exist, or execution details. It implies a non-destructive assessment but does not confirm it. The output description is helpful but lacks explicit transparency about side effects or limitations.
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, concise sentence that front-loads the core purpose and then lists the output components. It avoids unnecessary words and is easy to parse. It could be slightly more structured (e.g., bullet points) but is well within acceptable length and clarity.
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 tool's complexity (8 required enum parameters, no output schema, no annotations), the description is somewhat thin. It lists the returned items but does not explain what 'RAG' stands for, how to interpret the score, or how parameters influence outcomes. While the output list is helpful, the absence of parameter guidance and methodological context leaves room for ambiguity. Adequate but not complete.
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 0%, and the description does not mention any of the 8 parameters. The enum values are somewhat self-explanatory (e.g., 'office', 'pre1945'), but the description provides no guidance on how to select them or how they affect the result. Since the schema carries no descriptions, the description must compensate, but it does not, leaving the agent to rely solely on enum names. This is a significant gap.
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's purpose: 'Building Readiness assessment for change-of-use / conversion.' It specifies the verb (assessment), the resource (building readiness), and the context (change-of-use/conversion). It also lists the output components (score, complexity, four domain scores with RAG, recommendations), making it distinct from other assessment tools in the sibling list.
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 implies the usage context—'for change-of-use / conversion'—but does not explicitly state when to use this tool versus alternatives or provide any exclusions. It does not name sibling tools or give conditions for selection, so an agent must infer when this is the right choice. Adequate but not proactive.
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.
