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Agentic House Search

by io.github.asturksever

Compare UK postcodes side by side

postcode_compare
Read-onlyIdempotent

Compare two to five UK postcodes on chosen categories, aligned measure by measure.

Fetches each postcode's report concurrently and lines the facts up in a table, so you can answer "which of these is better connected / quieter / cheaper" in one call instead of several.

Args:

  • postcodes (string[]): 2-5 UK postcodes

  • categories (string[]): 1-6 of demographics, crime, deprivation, prices, broadband, mobile, noise, transport, amenities, schools, environment

  • response_format ('markdown' | 'json'): default 'markdown'

Returns: One row per measure with a column per postcode, each cell carrying the value, its band, and the category status for that postcode. Caveats collect anything that makes a row not strictly comparable.

Comparability warnings you must respect, and which this tool surfaces:

  • Deprivation ranks from different UK nations are NOT comparable — different indices over different numbers of areas.

  • A measure missing for one postcode because the dataset does not cover that nation is not a low score; the cell says "out_of_coverage".

  • Ofcom mobile figures describe a whole local authority, so two postcodes in the same authority will always be identical.

  • Crime counts describe a 1 km square and depend on each police force submitting data; a very low count can be a gap rather than a quiet street.

Examples:

  • "Which has better broadband, SW11 1AA or M1 1AE?" -> postcodes=[...], categories=["broadband"]

  • "Compare these three on crime and schools" -> categories=["crime","schools"]

Don't use when: you have one postcode (use postcode_report) or want the underlying datasets (use postcode_search_datasets).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
postcodesYesTwo to five UK postcodes to compare, e.g. ["SW11 1AA", "M1 1AE"]
categoriesYesWhich categories to compare on. Keep it tight — comparing all eleven across five postcodes produces a very large answer.
response_formatNo'markdown' for a side-by-side table, 'json' for the structured comparisonmarkdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsYes
caveatsYes
postcodesYes
categoriesYes

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive hints. The description adds substantial behavioral context: concurrent fetching, output format, and critical comparability caveats (e.g., deprivation ranks not cross-nation comparable, mobile data at local authority level, crime data gaps). No contradictions with annotations.

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

Conciseness4/5

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

The description is well-organized with clear sections (Args, Returns, Caveats, Examples, Exclusions) and front-loaded with the core purpose. It is somewhat lengthy, but the length is justified by the tool's important comparability warnings and usage nuances.

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?

The description covers all relevant aspects: purpose, usage, parameter behavior, return format, caveats, and alternative tools. Even with an output schema available, it explains the table layout and limitations, making it fully complete for agent decision-making.

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 fully describes each parameter with constraints and enums (100% coverage). The description's Args section largely restates schema information; the only extra advice ('keep it tight') is also present in the schema. Thus the description adds minimal value beyond the schema.

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's function: comparing 2-5 UK postcodes side by side on selected categories. It names the specific verb 'Compare' and resource 'UK postcodes', and differentiates it from siblings by naming alternatives like postcode_report for single postcodes.

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

Usage Guidelines5/5

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

Explicit 'Don't use when' section provides clear exclusions with named sibling tools (postcode_report, postcode_search_datasets) and examples of appropriate use cases. This is exactly the guidance an agent needs to select the right 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

A4.7/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: compare does side-by-side multi-postcode analysis, report does a single-postcode deep dive, lookup resolves geography, search_datasets finds datasets, and get_dataset retrieves a full dataset entry. The descriptions explicitly cross-reference when not to use each tool, eliminating any ambiguity.

Naming Consistency5/5

All tool names follow a consistent pattern: lowercase snake_case with a 'postcode_' prefix followed by a verb_noun (compare, get_dataset, lookup, report, search_datasets). No mixed conventions or vague verbs like 'process' or 'execute'.

Tool Count5/5

At 5 tools, the set is tightly scoped for a UK house-search data server. Each tool covers a distinct operation (lookup, report, compare, dataset search, dataset details) and neither feels redundant nor bloated. This is well within the ideal 3-15 range.

Completeness5/5

The tool set provides a full workflow: look up a postcode's geography, get a comprehensive neighbourhood report, compare multiple postcodes, search for external datasets to fill gaps (e.g., EPC, flood risk), and retrieve full dataset details. There are no dead ends; every tool has a clear follow-up and the coverage matches the stated purpose.

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