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Long-held, high-equity properties

long_held_high_equity
Read-onlyIdempotent
Long-held properties in an area carrying a large paper gain — the classic
off-market cohort, ordered by gain rather than by value.

Typical output for a London district: mid-1990s purchases at £23,000-37,000
now valued at £566,000-758,000.

`area_id` is the marts area id from `area_resolve`.

UK only. Costs 40 credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
area_idYes
min_yearsNo
min_gain_pctNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, openWorldHint=false, so the safety profile is covered. The description adds genuine context beyond that: a credit cost, a UK-only constraint, and the gain-based ordering. It doesn't disclose pagination or result-size behavior, which limits it to a solid 3.

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 paragraphs, front-loaded with the cohort definition and ordering rule, then a concrete output illustration, then the prerequisite/constraint/cost facts. Every sentence carries distinct information.

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?

An output schema exists, so return values need not be described, and the behavioral facts (cost, geography, prerequisite, ordering) are present. However, with 0% schema coverage and three undocumented parameters, an agent still lacks the meaning of min_years, min_gain_pct, and limit.

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

Parameters2/5

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

Schema description coverage is 0% across four parameters, so the description carries the full burden. It only clarifies area_id (its source is area_resolve); limit, min_years, and min_gain_pct are left entirely unexplained in both schema and prose, even though their concepts underpin the tool.

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 states a precise cohort (long-held properties in an area carrying a large paper gain), a specific ordering rule ('ordered by gain rather than by value'), and frames it as the 'classic off-market cohort.' An agent can distinguish this from siblings like equity_estimate or sourcing_offmarket_owners from the text alone.

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 names the prerequisite (area_id comes from area_resolve), scopes geography ('UK only'), and discloses cost ('40 credits'). It never explicitly names an alternative tool or a when-not-to-use condition, so it falls short of a 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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