Construction daily-log generation, jurisdiction compliance requirements, construction FAQs.
Scored across 3 tools
Each tool has a clearly distinct purpose: generating a template, retrieving compliance requirements, and searching an FAQ. There is no meaningful overlap that would cause an agent to select the wrong tool.
All three tools follow a consistent verb_noun pattern: create_daily_log_template, get_logging_requirements, and list_construction_faq. The convention is predictable and readable.
Three tools is reasonable for a narrowly scoped logging-reference server, though it is on the thin side. Each tool earns its place, but the surface feels minimal.
The tool set covers template generation, requirements lookup, and FAQ search but omits core log lifecycle operations such as saving, retrieving, updating, or deleting daily logs. These gaps may force agents to use external tools for actual log management.
Generate a construction daily log template.
| Name | Required | Description | Default |
|---|---|---|---|
| project_type | No | Type of construction project the daily log template is for, e.g. residential, commercial, infrastructure. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and openWorldHint=false, so the safety profile is covered. The description adds essentially nothing beyond the name—no indication of what the generated template contains, its format, or whether the optional project_type changes the output.
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?
One front-loaded sentence with zero waste. It is efficient, though the brevity comes at the cost of omitted detail rather than 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?
The tool is simple (one optional param, rich annotations, no output schema), so the description is minimally adequate. However, it never says what the returned template looks like or what effect project_type has, leaving an agent unable to predict the result.
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?
With a single parameter at 100% schema description coverage, the schema fully documents project_type and its examples. The description adds no semantics beyond that, so the baseline 3 applies.
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?
States a specific verb (Generate) and resource (construction daily log template), so an agent knows exactly what it produces. It does not differentiate itself from siblings like get_logging_requirements, which may retrieve related information.
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 on when to use this versus get_logging_requirements or list_construction_faq, nor any prerequisites or exclusions. The agent must infer the routing decision entirely on its own.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get daily log compliance requirements.
| Name | Required | Description | Default |
|---|---|---|---|
| project_type | No | Type of construction project to look up daily log compliance requirements for, e.g. residential, commercial, infrastructure. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint, idempotentHint, openWorldHint=false, and destructiveHint=false, so the description needs to add context rather than restate safety. It adds nothing about the shape of the returned requirements, whether requirements vary by day, or what happens when project_type is omitted, which matters because no output schema exists.
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?
A single short sentence with the resource front-loaded and no filler. It is efficient, though the brevity edges into under-specification rather than genuine density.
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 one-parameter read-only lookup with full schema coverage and complete annotations, the description is adequate: it says what is fetched. It is not complete on its own, since it does not explain the default when project_type is omitted or what the requirements look like, and there is no output schema to fill that gap.
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% and the single project_type parameter is fully documented in the schema, including examples (residential, commercial, infrastructure). The description contributes no additional semantics, such as the effect of omitting the optional parameter, so the baseline 3 applies.
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?
States a specific verb plus resource: fetching daily log compliance requirements. That is clear enough to distinguish it from create_daily_log_template (a write) and list_construction_faq (a general FAQ lookup), though the description never actually names or contrasts those siblings.
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 call this versus create_daily_log_template, and no mention of prerequisites or of what to do with the result. The 'daily' qualifier and the project_type parameter imply a lookup-before-logging workflow, but the agent has to infer that.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search construction logging FAQ.
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | Search keywords for the construction logging FAQ, e.g. overtime rules, safety incidents. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, non-destructive, and closed-world, so the safety profile is fully covered. The description adds nothing on top of that: no mention of result volume, ranking behavior, or what happens when the query is omitted despite the parameter being optional.
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?
It is a single front-loaded sentence with zero padding, which is structurally sound. However, the brevity crosses into under-specification rather than economy, so it doesn't earn a high conciseness score.
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 is simple (one optional string, rich annotations, no output schema), so a short description is defensible. Still, the missing routing guidance against get_logging_requirements and the unanswered question of behavior with no query leave real gaps for an agent deciding whether to call it.
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?
With a single parameter at 100% schema description coverage (including examples "overtime rules", "safety incidents"), the schema already carries the semantics. The description adds no guidance on query syntax, matching behavior, or what an empty query returns, so the baseline 3 applies.
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?
"Search construction logging FAQ" gives a verb (Search) and a resource (construction logging FAQ), so the basic intent is legible. But it is nearly a verbatim restatement of the title "Search Construction FAQ" and offers no differentiation from siblings like get_logging_requirements, so an agent can't tell from the description alone which one answers a question.
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 statement of when to use this tool versus get_logging_requirements or create_daily_log_template, and no prerequisites or exclusions. The agent must infer the routing decision from tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
create_daily_log_template2 fields changedInput schema / properties / project_type / descriptionAdded value: +"Type of construction project the daily log template is for, e.g. residential, commercial, infrastructure."Input schema / properties / project_type / examplesAdded value: +[
+ "residential",
+ "commercial",
+ "infrastructure"
+]get_logging_requirements2 fields changedInput schema / properties / project_type / descriptionAdded value: +"Type of construction project to look up daily log compliance requirements for, e.g. residential, commercial, infrastructure."Input schema / properties / project_type / examplesAdded value: +[
+ "residential",
+ "commercial",
+ "infrastructure"
+]list_construction_faq2 fields changedInput schema / properties / query / descriptionAdded value: +"Search keywords for the construction logging FAQ, e.g. overtime rules, safety incidents."Input schema / properties / query / examplesAdded value: +[
+ "overtime rules",
+ "safety incidents"
+]create_daily_log_templateget_logging_requirementslist_construction_faqCompliance answers for 10 construction trades in AU, UK, US, CA and EU: codes, licensing, RAMS.
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