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lts_expiry_risk

Find LTS records expiring within a given number of days. Returns records sorted by urgency (soonest first) with days remaining, plus summary counts by region and developer. Use for compliance monitoring, renewal pipeline tracking, and risk assessment. Capped at 25k rows; check truncated flag and narrow filters if true.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lawNoFilter by housing law: BP220 (socialized/economic) or PD957 (open market)
daysNoLook-ahead window in days from today (default 90)
regionNoFilter to a specific DHSUD region

Schema Changelog

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

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description fully discloses key behaviors: sorting by urgency, returning days remaining, providing summary counts by region/developer, and a 25k row cap with a truncated flag and advice to narrow filters. This exceeds typical disclosure and gives the agent critical operational knowledge.

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 sentences, each earning its place: purpose/returns, use cases, and capacity warning. The description is front-loaded and free of fluff.

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

Completeness5/5

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

Despite no output schema, the description explains return structure (sorted, days remaining, summary counts, truncated flag) and operational limits (cap, filter advice). It's complete 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.

Parameters4/5

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

The schema covers 100% of parameters, so baseline is 3. The description adds context by linking the 'days' parameter to the expiry window and mentioning 'narrow filters,' which implicitly describes how to use region/law parameters. It reinforces but doesn't duplicate schema details.

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 clearly states the tool finds LTS records expiring within a specified timeframe, using a specific verb ('Find') and resource ('LTS records'). It differentiates from sibling tools by emphasizing expiry risk, urgency sorting, and summary counts, making its purpose distinct.

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?

It explicitly names use cases: 'compliance monitoring, renewal pipeline tracking, and risk assessment.' While it doesn't mention alternative tools or exclusions, the context is clear and sufficient for an agent to decide when to invoke this tool.

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