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

With no annotations, the description must disclose behavior. It does mention key outputs and notes that the renovation cost is an estimate, which adds some transparency. However, it does not explain methodology, assumptions, limitations, or how 'deadline pressure' is calculated, leaving room for misinterpretation.

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 efficiently communicates the core purpose and main results. Every phrase adds value without unnecessary padding.

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 7 required parameters and no output schema, the description is incomplete. It does not explain what the compliance score means, the scale of the deadline pressure, how measures are prioritized, or any limitations of the assessment. Sibling tools suggest alternative compliance contexts, and the description fails to position EPBD against them.

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 43%, and the description adds no parameter-specific meaning. It does not mention how inputs like building_type, year_built, current_epc, or has_solar_pv affect the assessment, leaving the agent to rely on minimal schema hints.

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 assesses EU EPBD (2024) compliance, which is a specific regulation and action. It also lists concrete outputs (compliance score, renovation cost estimate, deadline pressure, priority retrofit measures), distinguishing it from sibling tools like MEES checker or UK planning checker.

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?

No guidance is provided on when to use this tool versus alternatives. It does not specify prerequisites, such as EU location or building type, nor does it mention when to prefer other compliance assessment tools among the siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations are provided, so the description carries the burden. It discloses what the tool returns (per-scope tCO2e, intensity, etc.) and mentions the CRREM stranding check and embodied carbon, implying a calculation/assessment. However, it does not state any assumptions, limitations, or whether it requires additional data not listed in the schema. The read-only nature is implied by 'returns' but not explicitly stated.

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, well-organized sentence that front-loads the primary purpose and then enumerates key outputs. No redundant or filler content. It is as concise as possible while conveying essential information.

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 (10 parameters, 4 required, no output schema) and the lack of annotations, the description is too brief. It lists output categories but does not explain input requirements, calculation scope, or how to interpret results. This makes the tool's full capabilities ambiguous, especially when compared to sibling tools with more detailed descriptions.

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%, meaning the description adds no information about the 10 input parameters. The tool requires 4 parameters (building_type, floor_area_m2, location, year_built) but the description never mentions what inputs are needed or how they influence the result. This is a critical gap for an agent deciding how to invoke the tool.

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?

Description clearly identifies the tool as a building carbon footprint assessment covering Scope 1/2/3, CRREM stranding check, and embodied carbon. It lists specific outputs (per-scope tCO2e, intensity, CRREM compliance, net-zero gap, priority actions), distinguishing it from generic tools like calculate_carbon and precondition tools like sap_sbem_precheck.

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?

No guidance is provided on when to use this tool versus alternatives. The description does not mention exclusions, prerequisites, or use-case boundaries. With many sibling tools in the sustainability/building assessment domain, the agent receives no direction on selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description bears full responsibility for disclosing behavior. It details the return payload (score, complexity, domain scores, RAG, recommendations), which is helpful, but it does not mention permissions, data sources, or whether the operation is read-only. The lack of input-side behavior guidance leaves a transparency gap.

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 sentence that efficiently packs purpose and output details without redundancy. It is front-loaded with the core intent and then lists the output pieces, making it easy to parse.

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, the description is under-specified. It gives a high-level output summary but omits input parameter semantics, interpretation of the RAG ratings, and how the score is derived. The agent would need to infer or probe to use the tool correctly.

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 compensate. It never mentions the eight parameters (current_use, proposed_use, year_built, etc.), their meaning, or how they influence the readiness assessment. The enums alone do not explain the business logic, leaving the agent with no semantic guidance.

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 it performs a 'Building Readiness assessment for change-of-use / conversion' and enumerates the specific outputs (0-100 readiness score, complexity, four domain scores, recommendations). This distinguishes it from sibling tools like dgnb_bim_readiness, which likely focus on broader readiness or specific standards.

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?

It implies the tool is intended for change-of-use or conversion projects but does not explicitly state when to use it over alternatives or mention any exclusions or prerequisites. No alternative tools are referenced, so the guidance is only implicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the burden of behavioral disclosure. It states what the tool returns (carbon intensity, benchmark, reduction measures with payback) and the methodology, but lacks details on assumptions, limitations, or handling of missing inputs (e.g., when energy_kwh_year is 0). It is not misleading but incomplete.

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, focused sentence that front-loads the action and includes key outputs. No extraneous 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?

The tool has 5 parameters, no output schema, and no annotations. The description covers the core purpose and returns, but misses usage context, prerequisites, limitations, or methodology nuances. It is adequate but not comprehensive given the tool's complexity.

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 covers 60% of parameters, leaving floor_area_m2 and construction_year undocumented. The description does not explain any parameters directly, nor does it compensate for the gaps. It implies operational vs. embodied inputs but does not clarify how each parameter is used.

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 with a specific verb ('Calculate') and resource ('operational + embodied carbon and net-zero gap'), and references specific standards (CIBSE TM65 / RICS WLCA). This distinguishes it from sibling tools like building_carbon_footprint by emphasizing the net-zero gap and payback measures.

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?

No guidance is provided on when to use this tool versus alternatives. Sibling tools include similar carbon-related calculators (e.g., building_carbon_footprint), but the description does not mention scenarios where this tool is preferred or excluded.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations are provided, so the description must disclose behavior. It discloses the return values (PUE score, efficiency rating, annual cost estimate, engineering recommendations), which is helpful. However, it does not state that the tool is read-only, nor does it describe assumptions, error handling, or limitations. The behavioral disclosure is partial.

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 purpose and includes a brief list of outputs. There is no redundant or unnecessary language, and every phrase adds value.

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?

Since there is no output schema, the description correctly lists the return items. It covers the inputs via schema and outputs via description, which is sufficient for a straightforward calculation tool. It could elaborate on the meaning of 'efficiency rating' or 'annual cost estimate', but that is not essential for correct invocation.

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 input schema provides 100% coverage for all four parameters with examples, so the description does not need to add parameter-level detail. The description adds no semantics beyond the schema, which aligns with the baseline of 3 for high schema coverage.

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 states a specific action ('Calculate') and a specific resource ('Power Usage Effectiveness (PUE) for a data centre or server room'), and explicitly lists outputs (PUE score, efficiency rating, annual cost estimate, engineering recommendations). This clearly distinguishes the tool from siblings like 'calculate_carbon' or 'estimate_cooling_load'.

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 clearly identifies the context for use ('data centre or server room') but does not explicitly mention when to avoid using it or provide alternative tool suggestions. It gives a clear usage context without exclusion criteria, matching the 'clear context, no exclusions' level.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description must carry the full burden for behavioral disclosure. It lists return values (feasibility score, timeline, etc.) but does not disclose assumptions, limitations, whether it's a preliminary assessment, or any regulatory caveats. For a feasibility tool, this lack of caveat context is a significant gap.

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 sentence, front-loaded with the main verb and resource, and lists the key outputs without waste. It is concise and efficiently structured.

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?

The description provides a reasonable overview of the tool's purpose and outputs, and names the UAE utility authorities, which gives some domain context. However, there is no output schema, so the list of return values lacks detail (e.g., scoring scale, format of timeline). For a complex assessment with six required inputs, the description is adequate but incomplete.

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 six parameters. It fails to compensate by explaining what inputs are needed, how they affect the assessment, or what values are expected. Parameter names are somewhat self-explanatory, but the description adds no extra meaning beyond the schema's types/enums.

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 the specific verb 'Assess' with a clear resource: 'UAE grid connection feasibility' and names the relevant authorities (DEWA/ADDC/SEWA/FEWA). This distinguishes it from sibling tools like check_uae_bim_compliance or uae_climate_ghg, making the purpose unambiguous.

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?

Usage is implied from the verb and resource—if you need UAE grid connection feasibility, this is the tool. However, there is no explicit when-to-use vs. alternatives, nor any exclusion criteria. The description does not mention when not to use it or point to a specific alternative.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description carries the burden of disclosing behavioral traits. The verb 'Assess' suggests a read-only analysis, and the description lists the computed outputs. However, it does not explicitly state that the tool has no side effects, does not modify data, or does not require any permissions. It also doesn't disclose whether it performs external lookups or calculations only. The provided outputs add some transparency, but the lack of explicit safety guarantees keeps this at a moderate score.

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, dense sentence that front-loads the purpose and lists key outputs. Every word earns its place, with no fluff or redundant phrasing. It is an excellent model of concise yet informative writing.

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?

This is a complex tool with 11 input parameters, no output schema, and no annotations. The description only lists the outputs at a high level, but does not explain the meaning of the inputs, the range of the compliance score, what 'maturity level' refers to, or how the remediation actions are prioritized. For an agent to use this correctly, it would need more guidance on parameter interpretation and expected output format. The description is insufficient for the tool's complexity.

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 input schema has 11 parameters but only 1 (sector) has a description, giving 9% coverage. The tool description does not explain any of the parameters, nor does it clarify expected values beyond what the names imply. While some names are self-explanatory (e.g., has_ciso), others like has_board_reporting or has_ot_policy could benefit from further detail. Given the low schema coverage and zero compensation in the description, this dimension scores poorly.

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 specifies a concrete action ('Assess') and a precise resource ('NIS2 Directive (EU 2022/2555) compliance readiness'). It also lists distinct outputs (compliance score, maturity level, fine exposure, remediation actions), making it highly specific. It is clearly differentiated from sibling tools like check_uae_cybersecurity, which targets a different regulation.

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 a clear use case: assess an organization's readiness against the NIS2 Directive. While it doesn't explicitly mention alternatives or when not to use, the context is unambiguous. The tool is specifically for NIS2, so an agent would know when to choose it. No exclusions are stated, but none are necessary given the narrow scope.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description carries the full burden. It discloses the tool is a check/analysis operation that returns specific outputs, implying read-only behavior. However, it does not describe any limitations, unsupported cases (e.g., emirate 'other'), or other behavioral caveats, leaving some ambiguity.

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 sentences, front-loaded with the core purpose and followed by a clear list of return values. No wasted words, all sentences contribute to understanding.

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?

Despite listing the return values, the description lacks explanations for the domain-specific mandate criteria, the meaning of the compliance score, or how the input parameters affect the result. With 8 required parameters, no annotations, and no output schema, the description is too brief to fully prepare an agent for correct invocation in this complex domain.

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 provides no additional context for any of the eight required parameters. It does not mention building area, floors, emirate, building type, BIM model, software, IFC export, or BEP, leaving the agent to rely solely on schema types/enums without guidance on their purpose in the compliance check.

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 specific action ('Check UAE BIM mandate applicability') and the relevant regulatory context (Dubai Circular 196, Abu Dhabi DMT, Sharjah). It distinguishes from sibling tools by being uniquely focused on UAE BIM compliance, and further clarifies the tool's output (mandate status, compliance score, required LOD, submission checklist).

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: it is for checking UAE BIM mandate applicability in specific emirates. It does not explicitly mention alternatives or exclusions, but the context is sufficient for an agent to decide when to use this tool versus other unrelated tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the burden of disclosing behavior. It does disclose what the tool returns (applicable framework, compliance score, critical gaps, mandatory controls), which is useful. However, it does not explicitly state that the assessment is read-only or if any side effects exist, leaving some ambiguity for a tool with no annotation hints.

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?

Two sentences: the first states purpose, the second lists return values. No waste, front-loaded with the core action, and the structure is logical and efficient.

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 8 required parameters, no output schema, and only 13% schema coverage, the description is too sparse. It does not explain how to supply inputs, what the compliance score means, or how to interpret the results, leaving significant gaps for a tool of this complexity.

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 explain any of the 8 required parameters. Most parameters (e.g., has_isms, has_vulnerability_assessment) are left without narrative explanation, so an agent cannot infer their meaning or required format. The description fails to compensate for the low schema coverage.

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 with a specific verb ('Assess') and resource ('UAE cybersecurity regulatory compliance'), and names the exact frameworks (NESA IAS, Dubai ISR, CBUAE, TDRA), distinguishing it from sibling tools like check_nis2_readiness (EU) and check_uae_bim_compliance (building compliance).

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's scope is clear from the frameworks listed, making it obvious this is for UAE-specific cybersecurity compliance. However, it does not explicitly provide when/when-not guidance or name alternative tools, so it lacks the explicit exclusions of a top guide.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the full burden. It discloses key behaviors: it computes a score, flags blocking (critical) failures, returns recommended additional checks, and explicitly disclaims being a formal due-diligence report. This gives the agent a clear expectation of the tool's output and limitations, though it could further detail the score's interpretation or output format.

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 concise, using just two sentences. The first sentence states the core function and scope, and the second adds behavioral details and a critical limitation. Every phrase earns its place with no redundant information.

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 moderate complexity (nested object, enum, no output schema), the description covers purpose, categories, behavior, and limitations, providing a solid overall understanding. However, without an output schema, it would benefit from describing the exact output structure or score range, making the description slightly incomplete for an agent to fully predict the tool's response.

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 input schema provides 100% description coverage, listing all question IDs and purpose enum values. The tool description adds contextual meaning by linking categories (financial, technical, cyber, energy) to the answers and explaining how the purpose parameter relates to NIS2/EPBD, which enriches the schema and helps the agent map inputs to the tool's intent.

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 function: computing a vetting score for contractors using a 12-question checklist across NIS2/EPBD categories. It distinguishes itself from sibling tools by focusing on contractor vetting rather than general readiness or assessment, and the specific mention of financial, technical, cyber, and energy categories adds precision.

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 for when to use the tool (contractor vetting for NIS2/EPBD) and includes an explicit exclusion ('Not a formal due-diligence report'), indicating when not to use it. However, it does not name alternative tools or provide detailed when-to-use/when-not-to-use scenarios, so it falls short of maximum guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries full burden. It discloses the tool's behavior: it performs a self-assessment and returns specific outputs (pre-score, certification level, BIM level, domain breakdown, gaps). It also states a limitation ('Not a formal DGNB audit'), which helps set expectations. It doesn't mention authorization needs or side effects, but for a read-only self-assessment tool, this is sufficient transparency.

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 sentences, front-loaded with the main purpose and immediately followed by return values and a caveat. Every sentence adds value: the first defines what the tool does and how, the second states outputs and a key limitation. Zero waste.

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 has nested objects, an enum, and no output schema, the description provides a complete picture of what the tool returns (pre-score, level, BIM level, breakdown, gaps) and its scope (20-question checklist, non-formal). It is sufficient for an agent to understand the tool's function. However, it lacks guidance on when to use this vs. directly related siblings (e.g., check_uae_bim_compliance), which slightly reduces completeness.

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 coverage is 100%: 'answers' has a detailed description listing all question IDs, and 'cert_target' has an enum and description. The tool description adds context about the checklist ('20-question') but does not explain parameter formats or semantics beyond what the schema already provides. Thus, the baseline of 3 is appropriate since the schema does the heavy lifting.

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 function: 'DGNB certification pre-score and BIM (ISO 19650) maturity self-assessment' with a specific verb (pre-score) and resource (DGNB/BIM maturity). It distinguishes itself from sibling tools by focusing on DGNB + ISO 19650 and explicitly notes it is 'Not a formal DGNB audit', setting it apart from other assessment tools.

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 for use: a self-assessment via a 20-question checklist, returning pre-score and gaps. It offers an explicit exclusion ('Not a formal DGNB audit'), implying it is for preliminary screening rather than official certification. However, it does not name alternative tools or provide when-to-use/when-not-to-use guidance, so it lacks the explicit alternatives required for a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the burden of behavioral disclosure. It adds 'Indicative' as a caveat about accuracy, but does not detail other traits such as whether outputs are estimates, how to interpret cost ranges, or potential variability. It gives a clear overview of what is produced but lacks deeper limitations or operational context.

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, compact sentence that immediately communicates the core purpose and key output components. No repetitive or extraneous text, making it highly efficient.

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?

The description communicates the main deliverables (roadmap phases, cost ranges, energy savings, EPC trajectory) but does not describe the return format or structure, and does not explain optional parameters like era, address, or building_type. Given the tool's moderate complexity and no output schema, more detail on the resulting structure would improve completeness.

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 100%, so the baseline is 3. The description mentions 'from current EPC, floor area and heating type', which reinforces the required inputs but does not add new meaning beyond the schema. It does not clarify units, enums, or any additional parametric detail.

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 as a staged digital renovation passport under EPBD-style guidelines, specifying a 3-phase roadmap with cost ranges, energy savings, and EPC trajectory. This is a specific and distinct function compared to sibling tools like mees_checker or heatpump_heatloss.

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 use for generating renovation roadmaps based on EPC, floor area, and heating, but does not explicitly state when to prefer this over alternatives or list exclusion criteria. Sibling tools are many, and no direct comparison is made, leaving usage somewhat implicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the burden of behavioral disclosure. It states the tool determines scope and computes KPIs, implying a read-only calculation. The note 'the regulation mandates reporting, not target values' adds important context about what the tool does NOT do (evaluate performance against targets). This is meaningful behavioral transparency beyond mere 'calculates'.

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 three sentences, front-loaded with the tool's name and regulatory basis. Every sentence adds value: scope determination, KPI computation, and the crucial caveat about target values. No filler or repetition of schema content.

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 calculation tool with no output schema, the description adequately covers what it computes and the regulatory context. It lacks an explicit statement of return format, but the phrase 'reporting pack' implies a structured result set. Given the tool's moderate complexity, this is sufficiently complete, though not perfect.

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?

While the schema already describes each parameter individually, the description ties parameters to the KPIs (e.g., water_input_m3 → WUE, reused_heat_kwh → ERF, renewable_energy_kwh → REF) and highlights the scope threshold (it_power_kw >= 500 kW). This adds integrative meaning over the schema's isolated descriptions, more than the baseline 3.

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 function: it determines reporting scope for EU EED data centres and computes specific KPIs (PUE, WUE, ERF, REF). It names the exact regulation and distinguishes itself from simpler sibling tools like calculate_pue by covering a broader, regulation-specific pack.

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 for when to use: for EU EED data-centre reporting, with a scope threshold (IT power >= 500 kW). It does not explicitly name alternatives or exclusions, but the regulatory and threshold context makes the intended use obvious, so it earns a 4 rather than a 3.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations are provided, so the description carries the full burden. It discloses the calculation methodology and explicitly lists the return values (required capacity, installed capacity with redundancy, system recommendation, annual energy). This is meaningful behavioral context, though it omits assumptions or caveats about inputs.

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 sentences, front-loaded with the core purpose, and each sentence contributes value. It is concise with no 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?

With six required parameters, low schema coverage, and no output schema, the description is too thin to fully equip an agent. It lists outputs but does not explain parameter meanings, relationships between inputs and outputs, or any domain-specific constraints.

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 17% (just it_load_kw), and the tool description adds no parameter-level explanation. Five of six parameters lack any descriptive guidance, and the description does not compensate for the gaps.

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 'Estimate' and resource 'cooling load', and adds methodology (CIBSE Guide B2 / ASHRAE) plus a clear list of return values. However, it does not explicitly distinguish from the overlapping sibling tool 'thermal_load', so it stops short of full sibling differentiation.

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, no exclusions, and no mention of related tools like 'thermal_load' or 'calculate_pue'. The usage context is only implied by the tool's name and description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the full burden. It discloses that results are parametric and indicative, explicitly recommends validation against current cost indices, and defines the output shape (ranges and breakdown). It does not discuss underlying data sources or methodology, but the indicative caveat is a meaningful limitation that helps set expectations.

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 sentences long. The first sentence states the tool's purpose and scope, and the second states the returns and caveat. Every sentence is informative, with no filler or redundancy, and the key purpose is front-loaded.

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 no output schema and seven parameters, the description provides essential context: the region, the cost drivers, the nature of the output (ranges and breakdown), and a validation caveat. It lacks explicit currency or breakdown details, but overall it is enough for an agent to invoke the tool correctly for a preliminary cost estimate.

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 input schema has descriptions for only 3 of 7 parameters (43% coverage). The description lists the parameter categories in the first sentence, indicating they are cost factors, but it does not explain each parameter's role, units, or how they affect the estimate. It adds conceptual context but falls short of fully compensating for the low schema coverage.

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 a specific verb context ('Parametric construction cost benchmark') and defines the geographic scope (UK/EU/GCC) and the key cost drivers (country, project type, specification, procurement, programme, BIM). It also specifies the outputs (per-m2 and total cost ranges plus a breakdown), which distinguishes it from sibling tools in structural, BIM, or energy domains.

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 usage for parametric cost benchmarking in UK/EU/GCC, with the closing caveat 'Indicative parametric estimate, validate against current cost indices' clarifying it is for early-stage estimates. It does not explicitly name alternative tools or provide when-not-to-use conditions, but the context is strong enough for a typical agent to decide when to invoke it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations are provided, so the description carries the full burden. It discloses that the tool is 'Indicative, not a stamped design' which sets expectations about authority, and it outlines the computations performed. This is sufficient for a calculation tool with no side effects, though it could mention read-only behavior explicitly.

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 three short sentences, front-loaded with the core purpose, followed by key capabilities and a caveat. Every sentence adds value with no redundancy or fluff.

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 9 parameters, no output schema, and no annotations, the description provides a solid overview: scope, materials, calculations, and caveat. It does not describe return values, but the calculations listed are sufficient to infer outputs.

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 input schema has 100% parameter description coverage, so the baseline is 3. The description does not add parameter-specific meaning beyond the schema, but it does mention general capabilities (e.g., material types, section selection) that align with parameters.

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: 'Preliminary Eurocode beam design (steel EC3 / composite / reinforced concrete EC2)' with specific actions (selects section, computes ULS bending/shear, SLS deflection, fire protection). It distinguishes itself from sibling eurocode_column_checker by specifying 'beam design' and material options.

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 signals appropriate usage via 'Preliminary' and 'Indicative, not a stamped design,' providing clear context for when to use (early-stage design) and when not to use (final stamping). It does not explicitly name alternatives but the context implies this is for preliminary checks only.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 does state the output variables (Ncr, slenderness, chi, NRd, utilisation) and the indicative, non-stamped nature. However, it does not mention assumptions, default parameter behavior, or what happens when required concrete parameters (depth, width, reinforcement) are omitted for RC materials. This leaves a noticeable gap.

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 sentences, front-loaded with the tool's purpose, followed by a concise output list and a clear caveat. Every sentence earns its place; there is no redundancy 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 tool has 9 parameters, no output schema, and no annotations, the description does a good job covering the return values and scope. It is mostly complete for a calculation tool, though it could be enhanced by explicitly noting the different input requirements for steel versus concrete and by referencing sibling tools. Still, the essential context is present.

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 100%, so the baseline is 3. The description itself does not enrich parameter meaning beyond the schema; it only mentions that the check covers steel and RC, which maps indirectly to parameters like section vs depth/width. It does not explain parameter combinations or units, but the schema already provides these details.

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 and resource: 'axial column buckling check' under Eurocode, explicitly distinguishing it from sibling tools like eurocode_beam_designer. It also names the applicable code sections (EC3 6.3.1, EC2 5.8) and material types (steel/RC), making the tool's function precise and unambiguous.

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 clearly states the tool is for column buckling checks under Eurocode for steel and RC, which implies when to use it over beam design tools. It also includes an exclusion ('not a stamped design'). However, it does not explicitly name alternative tools or provide explicit 'when not to use' guidance, so it stops short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description bears the full burden. It discloses the indicative/non-binding nature of the estimate and specifies the return structure: preliminary and full fee ranges, turnaround days, and a contact CTA. This goes beyond simply restating the tool name, though it does not address authentication or other potential side effects.

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 sentences: the first states the purpose, the second lists the outputs. Every word earns its place, and the structure front-loads the core functionality.

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?

The tool requires six parameters, has no output schema, and lacks any annotation guidance. The description provides only a high-level summary and does not explain parameter meanings, how inputs affect the quote, or what 'preliminary and full DD fee ranges' signify in practice. This is insufficient for an agent to confidently invoke the tool with correct inputs.

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 17% (only building_type has a description listing allowed values). The tool description mentions none of the six required parameters, so it adds no meaning beyond the raw schema. With such low coverage, the description was expected to compensate but fails completely.

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 opens with a specific verb and resource: 'Generate an indicative Technical Due Diligence (TDD) fee estimate.' It clearly differentiates the tool from siblings by focusing on fee quotation rather than technical checks, and enumerates exact return items (fee ranges, turnaround days, contact CTA).

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 tool's intended use is implied by its name and description—when a TDD fee estimate is needed—but no explicit when-to-use or when-not-to-use guidance is given, nor are alternatives named. The context is clear enough for a unique tool, but the description lacks direct usage boundaries.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the burden. It discloses that results are estimates based on typical values and that SCOP is 'indicative', setting clear expectations. It also lists the return values. However, it does not explicitly mention read-only nature or any permissions, but as a calculation tool this is less critical.

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?

Two sentences: the first states what the tool does and the second lists outputs. No redundant information, front-loaded with purpose.

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?

Despite 10 parameters and no output schema, the description covers the core purpose, standards, inputs, return values, and limitation ('not measured'). It could include more methodological detail or safety disclaimers, but overall it is sufficiently complete for a calculation tool.

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 coverage is 60%, with descriptions for many optional parameters. The description mentions key inputs (floor area, storeys, age band, location, glazing) and gives context (fabric + ventilation), but it does not add significant meaning beyond what the schema already provides, and slightly overstates input list by including optional fields as if all are required.

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 ('estimate') and resource ('whole-dwelling fabric + ventilation heat-loss') and clearly distinguishes from siblings by specifying 'for heat pump sizing' and citing standard BS EN 12831 / MCS. The return values (design heat loss, recommended output, SCOP, annual demand) further differentiate it.

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: it is for domestic whole-dwelling heat loss estimation for heat pump sizing. It implicitly indicates when to use (UK heat pump sizing) and hints at limitations ('Typical U-values/SCOP, not measured'), but does not explicitly name alternatives or exclusion scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the burden of behavioral disclosure. It clearly states that the EPC C uplift is 'advisory only' and not yet law, and it lists the return values (compliance, can-let, cost cap, penalties). This is transparent about the tool's behavior without needing to mention destructive operations, as it is a read-only check.

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 three sentences long, front-loads the purpose, and every sentence adds value. There is no filler, and the structure efficiently communicates scope, legal status, and outputs in a compact form.

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 simplicity (2 enum parameters, no output schema), the description is quite complete. It covers the legal context, the test threshold, the advisory nature of the future standard, and the returned data. It could mention data sources or limitations, but for a compliance checker, the essential information is present.

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 has 2 parameters with enums and 0% description coverage, so the description must compensate. It does provide context by referencing 'domestic and non-domestic' and 'EPC E minimum', which maps to the property_type and current_epc_band parameters. However, it does not explicitly name the parameters or explain their format, leaving the agent to infer from the schema. This is adequate but not highly compensatory.

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 names the tool as a MEES check for England & Wales private rented property, with a specific verb ('check') and resource. It distinguishes itself from sibling tools by highlighting the jurisdictional and regulatory scope (MEES, EPC E minimum) and the domestic/non-domestic coverage, which is unique among the listed tools.

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 on when to use the tool: for MEES compliance checks on private rented property in England & Wales. It explains the primary test (EPC E minimum) and the advisory nature of the 2030 C uplift. However, it does not explicitly state when not to use it or name alternative tools, so it falls just short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description carries full disclosure burden. It mentions the tool returns pass/fail, is 'indicative', and escalates to TM59 on failure. This gives useful behavioral context beyond the schema, though it does not discuss limitations in depth or input validation.

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 sentences, front-loaded with the core purpose, and includes necessary caveats and follow-up guidance without wasted words. Every clause adds value.

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 no output schema, the description clearly states the return value (pass/fail) and next step (TM59). It also defines the scope (UK AD O 2021, new residential, simplified method) and the two key checks (glazing area and ventilation area), which is sufficient for an agent to select and invoke the tool correctly.

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 33% (2/6 params), but the description clarifies that inputs relate to orientation, risk zone, cross vs single aspect, and free ventilation area. This adds meaning to most_glazed_facade, location_risk, cross_ventilation, and provided_free_area_m2, compensating for the sparse schema descriptions.

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 performs a UK Approved Document O 2021 simplified-method overheating check for new residential buildings, testing maximum glazing area and minimum free ventilation area. It is specific about the resource (AD O 2021) and action (overheating check), distinguishing it from siblings like thermal_load or heatpump_heatloss.

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 specifies it is a simplified-method check and notes that if it fails, it points to CIBSE TM59 modelling as an alternative. This provides clear context for when to use this tool versus a more detailed modelling approach, though it does not explicitly name sibling tools or state exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the burden of behavioral disclosure. It discloses that results are 'Indicative', details return values (required charge points, cable routes, minimum power, cost caps), and includes the specific '1-in-5 for non-residential' rule. This gives the agent a realistic expectation of outputs, but it could be more explicit about whether the tool requires any special permissions or has other side effects (though as a calculator, these are minimal).

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 sentences, front-loaded with the tool's purpose and scope, and every sentence adds value. It efficiently packs in applicable regulations, use cases, outputs, and a key calculation rule without waste.

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 calculator with no output schema and no annotations, the description does state what it returns and the key 1-in-5 rule. However, it lacks guidance on how required vs optional parameters should be combined (e.g., 'provide dwellings for residential, covered_car_park for non-residential'), which could lead to incomplete or incorrect invocations.

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 covers 60% of parameters with descriptions (dwellings, parking_spaces, covered_car_park), and the description adds context about building types and works types, plus the '1-in-5' rule for cable routes. However, it does not clarify the conditional relationship between building_type and parameters like dwellings or covered_car_park, leaving some ambiguity for the agent.

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 is a 'UK Approved Document S 2021 electric-vehicle charge-point requirement calculator' and specifies the scope (new build, major renovation, residential, non-residential). It also lists concrete outputs (charge points, cable routes, minimum power, cost caps), distinguishing it from sibling tools like generic carbon calculators or building readiness checkers.

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 explicitly defines the applicable scenarios ('new build and major renovation, residential and non-residential'), providing clear context for when to use the tool. It does not, however, mention exclusions or direct comparisons to alternative tools, so it stops short of a full 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals the tool returns a set of financial metrics, but doesn't explain the meaning of the 'verdict', any underlying assumptions, or that it is purely a calculation with no side effects. For a calculator, some of this is implied, but key behavioral context (e.g., limiters like efficiency_gain_pct <= 90) is missing.

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 concise (two sentences) and front-loads the calculator's purpose. However, 'Engineering ROI calculator' is redundant with the tool name, and the output list could be more structured. Still, it is efficient and without fluff.

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?

There is no output schema, no annotations, and incomplete parameter coverage. The description lists the return values but leaves the 'verdict' ambiguous and doesn't explain formulas, units, or constraints. For a tool with six inputs and no structured output metadata, the description is not sufficiently complete for an agent to fully understand its behavior.

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 coverage is only 50%, and the description adds no parameter semantics. It doesn't mention any of the six inputs or clarify ambiguous ones like team_size or hourly_rate. The schema descriptions for manual_hours and efficiency_gain_pct help, but the rest rely on self-evident names. The description should have compensated for the coverage gap but doesn't.

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 as an ROI calculator for engineering, with a specific list of outputs (current manual cost, annual saving, net benefit, ROI %, payback months, 3-year NPV, verdict). This distinguishes it from sibling calculators that focus on other engineering metrics.

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 no guidance on when to use this tool vs alternatives. It does not mention use cases, prerequisites, or that the tool is a pure read-only calculation. Sibling tools are similar calculators, so guidance would be valuable but is entirely absent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

The description discloses that this is a simplified precheck, not an official certification, and mentions using 'validated SAP 10 fuel factors' for credibility. It also notes the official band is 'cost-based', adding useful context beyond what annotations (which are absent) would provide. It does not describe return values or assumptions for edge cases.

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 three sentences long, with each sentence adding essential information: scope (UK SAP 10.3/SBEM), functionality (map and compute), and an important caveat. It is front-loaded with the tool's name as a keyword phrase and wastes no words.

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 moderate complexity (3 parameters, one nested object, no output schema), the description covers the core purpose and a key limitation. It mentions the 'and/or' nature of the two functions, which helps the agent understand usage combinations. However, it does not describe the output format or return values, which is a notable gap without an output schema.

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 already covers all three parameters with descriptions, achieving 100% coverage. The tool description paraphrases the schema by mentioning 'known SAP rating (1-100)' and 'fuel consumption', but adds no new semantic detail beyond that. It does not, for example, explain how floor_area_m2 is used in the calculation.

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 function with specific verbs: 'Maps' a SAP rating to an EPC band and 'computes' annual CO2 and primary energy. It uniquely identifies the UK SAP 10.3 / SBEM EPC context, which distinguishes it from sibling tools like assess_epbd_score or calculate_carbon.

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 usage for preliminary EPC assessments, noting it is a 'precheck'. It explicitly warns that the official EPC band requires a full SAP/RdSAP assessment, providing a clear exclusion. However, it does not name alternative tools or explicitly state when to choose this over them.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the full burden of disclosing behavioral traits. It lists outputs but does not explain the calculation methodology, assumptions, potential limitations, or whether this is a read-only estimation. The absence of any side-effect or prerequisite information leaves the agent without crucial context for a complex estimation tool.

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 sentence that efficiently conveys the tool's purpose and output list. It is not overly verbose, but it crams many outputs into one sentence, which slightly reduces scannability. Still, it earns a 4 for being compact and information-dense.

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?

This tool has 6 required parameters, 2 enums, low schema coverage, no output schema, and no annotations. The description provides only a high-level output list, omitting parameter explanations, usage context, and behavioral caveats. It is insufficient for an agent to invoke the tool correctly without additional information.

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 29%, and the description does not explain any of the 7 parameters. It only lists outputs, not inputs, so the agent gets no additional meaning about parameters like 'it_load_kw', 'ups_efficiency_pct', or 'cooling_type'. The tool relies heavily on the schema, which itself provides minimal descriptions.

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 is a 'Thermal Load Estimator' and enumerates specific outputs (heat load, cooling capacity, etc.), which conveys a concrete function. However, it does not explicitly differentiate from siblings like 'estimate_cooling_load' or 'calculate_pue', so it earns a 4 rather than 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?

No explicit guidance is given for when to use this tool versus alternatives such as 'estimate_cooling_load' or 'calculate_pue'. The mention of 'data centres / critical facilities' implies a context, but there is no when-to-use, when-not-to-use, or alternative recommendation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations provided, the description carries the full burden of disclosure. It honestly labels the result as an 'estimate' and notes that grid factors carry base-year/confidence caveats. However, it does not disclose what the output looks like, whether both scopes are always returned, or how optional gas parameters interact, leaving some behavioral aspects unclear.

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 sentences long, front-loaded with the core purpose, and immediately provides regulatory and caveat context. Every sentence contributes essential information with zero redundancy, making it concise and well-structured.

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 there is no output schema, the description omits any mention of the return format or how results are presented. It also doesn't explain how to choose between gas_m3 and gas_kwh or what happens when both are provided. While it includes useful regulatory and caveat context, these gaps prevent it from being fully complete for a 4-parameter tool.

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 coverage is 75% per context signals, so the schema already explains gas_m3 and gas_kwh. The description adds meaning to the 'emirate' parameter by mentioning emirate-specific grid factors, but it doesn't clarify the relationship between gas_m3 and gas_kwh or the units. It adds some value but not substantial beyond the 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 states the tool estimates UAE Scope 1 and Scope 2 GHG emissions from electricity and gas use, with a specific verb ('estimate') and resource ('GHG'). It differentiates from sibling tools by naming emirate-specific grid factors and the Federal Decree-Law context, making its scope unambiguous.

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 use for UAE mandatory reporting by mentioning the Federal Decree-Law context, but it does not explicitly state when to use this tool over alternatives like calculate_carbon or building_carbon_footprint. No exclusions or alternative suggestions are provided, so usage guidance is only implicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the burden. It discloses that the tool returns a verdict, applicable PD class, conditions, and flags, and adds the important caveat 'Indicative, verify with the LPA.' It doesn't detail data sources or error handling but provides essential behavioral expectations.

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?

Two sentences deliver scope, proposal types, outputs, and a caveat without waste. The information is front-loaded and each clause adds value.

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 no output schema, the description does a solid job of listing return elements (verdict, PD class, conditions, flags) and key input flags. It could be more explicit about unsupported inputs or parameter formatting, but it provides a clear overall picture for a planning rules engine.

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 30%, so the description must compensate. It mentions key concepts such as listed building, Article 4, conservation area, and AONB (matching flags), and it lists proposal types. However, it doesn't explain parameters like extension_depth_m units, property_type values, or the meaning of 'location' beyond the England scope, leaving gaps.

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 as a 'UK permitted-development (GPDO 2015, England) rules engine' with specific proposal types (extensions, loft conversions, change of use). It differentiates from sibling tools by focusing on planning/PD assessment rather than energy or structural topics, and specifies the geographic and regulatory scope.

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?

It establishes clear context: the tool applies to England under GPDO 2015 and to listed proposal types. However, it does not explicitly state when not to use the tool or reference alternative tools for other jurisdictions or non-PD matters, so guidance is good but not fully explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.