Check if a specific LTS number exists in the system. Returns whether it exists in lts_records, in project_lts, or both. Includes full record details when found.
| Name | Required | Description | Default |
|---|---|---|---|
| ltsNumber | Yes | The LTS number to look up (e.g., 'LS 0001234') |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It explicitly discloses the return behavior (whether the number exists in lts_records, project_lts, or both) and promises full record details when found. This gives an agent clear expectations, though it does not explicitly state that the operation is read-only or describe error behavior.
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 extremely concise—three short sentences that each add distinct information (purpose, sources checked, output details). It is front-loaded with the primary action and contains no redundant or ambiguous wording.
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 simple lookup with one parameter and no output schema, the description covers the essential aspects: what it does, which sources it checks, and what it returns when found. It does omit specifics about the 'not found' return format or any error conditions, but it is sufficiently complete for an agent to 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?
The input schema already provides 100% coverage for the single parameter ltsNumber, including an example format. The description only restates 'specific LTS number' and adds no new semantic details, so it meets the baseline but does not extend it.
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 action (check if a specific LTS number exists), the resources involved (lts_records, project_lts), and the output (existence status and full record details). This distinguishes it from sibling tools that search by city, developer, law, etc., making the purpose unmistakable.
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 when an exact LTS number is known and existence needs verification, but it does not explicitly state when to choose this tool over alternatives like lts_search or lts_by_*. There is no mention of when not to use it or direct comparisons to sibling tools, so guidance is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct aspect of LTS data (by city, developer, law, region, etc.) with no overlapping purposes. The descriptions clearly delineate their unique use cases.
All tools follow the consistent pattern 'lts_<descriptive_noun_or_phrase>' using snake_case. The naming is uniform and predictable, aiding agent selection.
With 12 tools, the set is well-scoped for a data query and analysis server. Each tool serves a clear function without redundancy or overload.
The tool set covers all necessary query dimensions (city, developer, law, region, expiry, stats, trends) and includes a search, check, and project-level view. No obvious gaps for a read-only analytics server.