Building carbon footprint (Scope 1/2/3) with CRREM stranding check and embodied carbon. Returns per-scope tCO2e, intensity, CRREM compliance, net-zero gap and priority actions.
| Name | Required | Description | Default |
|---|---|---|---|
| location | Yes | ||
| occupancy | No | ||
| year_built | Yes | ||
| refrigerant | No | ||
| gas_kwh_year | No | ||
| building_type | Yes | ||
| elec_kwh_year | No | ||
| floor_area_m2 | Yes | ||
| heat_kwh_year | No | ||
| renewable_pct | 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 provided, the description carries the full disclosure burden. It does reveal the output set and the main methodological concepts (per-scope tCO2e, CRREM compliance, net-zero gap, priority actions). However, it does not disclose assumptions around missing utility inputs, defaulting behavior, or calculation boundaries.
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 two tight sentences with no filler. The first sentence establishes the tool's purpose and scope, and the second enumerates the return values. Every phrase adds information and is front-loaded effectively.
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 a tool with 10 undocumented parameters, no annotations, no output schema, and an overlapping sibling, this description is incomplete. It covers the output side reasonably well but leaves input semantics, parameter relationships, defaults, and selection criteria entirely unaddressed.
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% with 10 parameters, and the description does not explain any of them. It never mentions building_type, floor_area_m2, location, year_built, elec_kwh_year, gas_kwh_year, renewable_pct, or how these map to scopes. The description fails entirely to compensate for the undocumented 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 clearly identifies the tool's domain: building carbon footprint with Scope 1/2/3, CRREM stranding, and embodied carbon, and it names the specific returns. It does not explicitly distinguish this from the overlapping sibling calculate_carbon, so it misses the differentiation needed for a 5.
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?
There is no guidance on when to use this tool versus alternatives such as calculate_carbon or assess_epbd_score. The description says what the tool computes, but not when it should be selected, what prerequisites exist, or when another sibling would be more appropriate.
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.
