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lts_records

Browse LTS records from DHSUD with filters. Shows normalized records with confidence levels. Filter by confidence (high/medium), linked status (has project_id), region, or text search. Use expiringWithinDays to find records expiring soon.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results
linkedNotrue = linked to project, false = unlinked
offsetNoPagination offset
regionNoFilter by region (use lts_filters to get valid values)
searchNoText search: project name, LTS number, or developer. Matched as a literal substring; use * as a wildcard. A term of only wildcards matches nothing
sortByNoSort fieldcreated_at
sortOrderNoSort directiondesc
confidenceNoFilter by data confidence level
expiringWithinDaysNoShow records with expiry date within N days from today

Schema Changelog

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

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

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations provided, the description carries the behavioral disclosure burden. It communicates that the tool is a read-oriented browse operation and that the output consists of normalized records with confidence levels. It does not mention pagination behavior, sort defaults, authorization requirements, or what happens when filters return no results, but for a browse tool this is a minimally acceptable disclosure.

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?

The description is three sentences with no filler. The main purpose is front-loaded, the output nature is stated, and the key filtering capabilities are summarized efficiently. Every sentence earns its place.

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

Completeness3/5

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

The description covers the core browsing and filtering behavior but omits several operational details that matter given the 9 parameters and no output schema: pagination defaults, sort options, and the shape of returned records beyond 'normalized.' It is sufficient for a simple call, but an agent would still need to rely on the schema for complete invocation context.

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

Parameters4/5

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 adds value by grouping parameters into meaningful filter categories, clarifying that 'linked' refers to having a project_id, and explaining the practical meaning of expiringWithinDays. This goes beyond the schema alone without duplicating it.

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

Purpose4/5

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

The description states a clear verb and resource: 'Browse LTS records from DHSUD with filters.' It further explains what the records contain (normalized records with confidence levels) and lists the main filter dimensions. It does not explicitly contrast itself with siblings like lts_search or lts_by_region, so it stops short of full differentiation.

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

Usage Guidelines3/5

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

The description clearly identifies the general use case: browsing and filtering LTS records, and even gives a specific pointer for expiringWithinDays. However, it never mentions when to prefer a sibling tool such as lts_search or lts_stats, nor does it state when not to use lts_records. Usage context is implied rather than explicitly contrasted.

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.

Resources