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lts_search

Search across DHSUD LTS records and published projects by name, LTS number, developer, or city. Returns matches from both lts_records and published projects. Universal entry point for LTS data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results per category
queryYesSearch term: project name, LTS number, developer name, or city. Matched as a literal substring; use * as a wildcard. A term of only wildcards matches nothing
offsetNoPagination offset

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedInput schema / properties / query / description
      Previous value: -"Search term: project name, LTS number, developer name, or city"New value: +"Search term: project name, LTS number, developer name, or city. Matched as a literal substring; use * as a wildcard. A term of only wildcards matches nothing"
  2. First observed

TDQS

A4/5.0
Behavior3/5

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

Without annotations, the description carries the behavioral burden, and it does disclose the important combined-source behavior: matches come from both lts_records and published projects. It does not describe result ordering, grouping, or pagination semantics beyond what the schema already states.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences each add distinct value: action and search fields, return scope, and positioning as the entry point. There is no filler or repetition of schema details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only search tool with all parameters documented in the schema, the description gives sufficient invocation context by defining the searched domains and result sources. The absence of an output schema is partially mitigated by the 'matches from both lts_records and published projects' statement, though a bit more return-format detail would make it fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already documents all three parameters at 100% coverage, including query substring/wildcard behavior and limit/offset defaults, so the baseline is 3. The description mostly restates the query parameter's accepted fields without adding new parameter-level detail.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific action and resource: 'Search across DHSUD LTS records and published projects' and names the searchable fields (name, LTS number, developer, city). The 'Universal entry point' phrase differentiates it from specialized siblings like lts_by_city and lts_by_developer.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Universal entry point for LTS data' plus the broad search scope clearly establishes this as the general-purpose search tool. It does not explicitly name when to avoid it and delegate to a specific sibling, 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.

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TDQS

A4.2/5.0
Disambiguation5/5

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.

Naming Consistency5/5

All tools follow the consistent pattern 'lts_<descriptive_noun_or_phrase>' using snake_case. The naming is uniform and predictable, aiding agent selection.

Tool Count5/5

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.

Completeness5/5

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.

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