Close Knit

Find similar areas

find_similar_areas

Read-onlyIdempotent

Neighbourhoods like one the user liked (crime, deprivation, income, price level and station access percentiles), optionally only cheaper ones: 'like this but cheaper / elsewhere'.

Input Schema

Name	Required	Description
`top_n`	No	How many areas to return.
`intent`	No	Optional, one to three sentences you write: what the user is looking for with this call and the criteria that matter, e.g. '2-bed rental near King's Cross, up to £2,500 a month, quiet, good primary schools'. Close Knit reads these to improve its answers. Your own summary, not the user's words or the chat; never names, contact details, exact addresses or family circumstances.
`area_id`	Yes	A neighbourhood (LSOA) the user liked.
`cheaper`	No	Only areas with a lower £/m² price level.
`bedrooms`	No	Adds a ballpark price for this size.
`rate_previous`	No	Optional: your rating of an earlier Close Knit answer, by the callId it carried. Send it with your next Close Knit call every time you have used an answer: rating 1-5 for how well it served the user's request, what was good, what was bad or missing, and the fix you would want.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedOct 27, 2026

addedInput schema / $defs

Added value: +{
+  "RatePrevious": {
+    "properties": {
+      "bad": {
+        "anyOf": [
+          {
+            "type": "string"
+          },
+          {
+            "type": "null"
+          }
+        ],
+        "default": null,
+        "description": "What was wrong, missing or confusing.",
+        "title": "Bad"
+      },
+      "call_id": {
+        "description": "The callId of the answer you are rating.",
+        "title": "Call Id",
+        "type": "string"
+      },
+      "fix": {
+        "anyOf": [
+          {
+            "type": "string"
+          },
+          {
+            "type": "null"
+          }
+        ],
+        "default": null,
+        "description": "The change to the tool or its answer you would want.",
+        "title": "Fix"
+      },
+      "good": {
+        "anyOf": [
+          {
+            "type": "string"
+          },
+          {
+            "type": "null"
+          }
+        ],
+        "default": null,
+        "description": "What was useful in the answer.",
+        "title": "Good"
+      },
+      "rating": {
+        "description": "1 = useless or wrong, 3 = usable with gaps, 5 = exactly what was needed.",
+        "title": "Rating",
+        "type": "integer"
+      }
+    },
+    "required": [
+      "call_id",
+      "rating"
+    ],
+    "title": "RatePrevious",
+    "type": "object"
+  }
+}

addedInput schema / properties / intent

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Optional, one to three sentences you write: what the user is looking for with this call and the criteria that matter, e.g. '2-bed rental near King's Cross, up to £2,500 a month, quiet, good primary schools'. Close Knit reads these to improve its answers. Your own summary, not the user's words or the chat; never names, contact details, exact addresses or family circumstances.",
+  "title": "Intent"
+}

addedInput schema / properties / rate_previous

Added value: +{
+  "anyOf": [
+    {
+      "$ref": "#/$defs/RatePrevious"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Optional: your rating of an earlier Close Knit answer, by the callId it carried. Send it with your next Close Knit call every time you have used an answer: rating 1-5 for how well it served the user's request, what was good, what was bad or missing, and the fix you would want."
+}

First observedOct 22, 2026

TDQS

A3.5/5.0

Behavior3/5

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

Annotations already cover read-only, idempotent, non-destructive, closed-world, so the safety burden is low. The description usefully discloses that similarity is computed over five named percentile dimensions and that 'cheaper' filters on £/m² price level — context not available elsewhere. It doesn't say how results are ranked or how many dimensions must align.

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?

A single dense sentence with the core action front-loaded and the similarity dimensions parenthesised so they don't bury the verb. Little waste, though the trailing quoted phrase is slightly cryptic ('elsewhere' is never defined).

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?

With an output schema, full parameter descriptions and read-only annotations, an agent has almost everything needed to select and call this correctly. The remaining gap is what 'elsewhere' means and whether results come back ranked by similarity.

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?

Schema coverage is 100%, so every parameter is already documented, and the baseline is 3. The description adds a little by framing area_id as 'one the user liked' and explaining the cheaper filter's basis, but top_n, bedrooms, intent and rate_previous get nothing extra.

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?

States a specific verb+resource: returns neighbourhoods similar to a given one, and names the exact similarity dimensions (crime, deprivation, income, price level, station access). It's clearly distinct in shape from rank_areas_by_metric or search_areas, though it never names those siblings to sharpen the contrast.

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 quoted trigger phrase 'like this but cheaper / elsewhere' implies when an agent should reach for this tool, and the 'cheaper' flag is flagged as optional. But there's no explicit statement of when NOT to use it or which sibling (match_areas, find_areas) handles the non-similarity case.

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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