Skip to main content
Glama

Verify listing claims

verify_claims
Read-onlyIdempotent

Grade spatial listing claims about travel times, nearby places, and distances against real routing and map data. Returns confirmed, stretched, false, or unverifiable verdicts for each claim.

Instructions

Grade spatial listing claims ("8 min to the metro", "shops on the doorstep", "green space nearby") against real routing and places data.

Free-text claim parsing needs an LLM — this tool takes already-decomposed
structured checks; the verify_listing_claims prompt teaches an agent how
to turn listing text into them. Each of claims (max 8; max 5 of kind
travel_time, since each costs a routed call) is one of:

- {"kind": "travel_time", "to_category": str|None, "to_name": str|None,
  "mode": "walk"|"cycle"|"drive" (default walk), "claimed_minutes": number}
  Finds the nearest place matching to_category (an Overture taxonomy
  slug) and/or to_name (a substring match), then routes to it and
  compares the routed minutes against claimed_minutes.
- {"kind": "count_nearby", "category": str|None, "name": str|None,
  "radius_m": number (default 500, capped at 2000), "claimed_at_least": int}
  Counts matching places within radius_m and compares against
  claimed_at_least.
- {"kind": "distance", "to_category": str|None, "to_name": str|None,
  "claimed_max_m": number}
  Straight-line distance (haversine, not routed) to the nearest match,
  compared against claimed_max_m.

Every kind needs at least one of its category/name fields; giving
neither is a bad_request. A category is an Overture taxonomy slug,
matched exactly (including its taxonomy descendants), never as a
substring — "park" does not match a parking garage; a name is a
substring match.

Verdict per claim: "confirmed" when the measured number is within the
claimed number x1.15 (count_nearby: measured count >= claimed),
"stretched" within x1.5 (count_nearby: count >= half the claim, floor
1), otherwise "false". A claim asserting a place exists at all, when
none is found within the search bound, is "false" with a note —
absence is a verdict, not an error. A claim the measurement cannot
decide is "unverifiable" instead of "false": a travel_time claim whose
place is found but cannot be routed to (no street graph nearby, or the
network doesn't connect the two points), or whose failing measurement
came from a size-cap-truncated street graph, and a count_nearby claim
whose claimed_at_least exceeds the row cap the count stopped at.

Returns {"results": [{"claim": <echo of the input>, "verdict":
"confirmed"|"stretched"|"false"|"unverifiable", "measured": {...
kind-appropriate minutes/count/distance_m, plus the matched place's id
and name when there is one}, "note": optional}, ...], "verdict_rule":
a one-line summary of the thresholds above}.

Returns a structured {"error": "bad_request", ...} for anything
malformed in claims (unknown/missing kind, more than 8 claims, more
than 5 travel_time claims, a missing or non-numeric claimed value,
neither target field given, or an unsupported mode), {"error":
"bad_request", ...} for invalid lat/lon, or a structured {"error": ...}
if the upstream dataset is unavailable or missing columns this tool
depends on.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYes
lonYes
claimsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Install Server

TDQS

A4.8/5.0
Behavior5/5

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

The description goes far beyond the annotations by detailing exact verdict thresholds (x1.15, x1.5), the semantics of 'unverifiable' vs 'false', how absence is treated, routing failure caveats, size-cap truncation effects, and structured error cases. This gives an agent a precise model of tool behavior that annotations alone could not provide.

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?

Although long, the description is densely informative and well-structured with bullets, bolded claim kinds, and clearly separated error/output sections. Every sentence adds a necessary behavioral or semantic constraint; there is no filler or repetition of schema/annotation data.

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?

This is a complex tool with three required parameters, no schema-level parameter descriptions, and many edge cases. The description covers input shape, claim constraints, matching semantics, verdict rules, output format, and all error classes. Given the complexity and the minimal schema, nothing essential is missing for an agent to invoke it correctly.

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

Parameters5/5

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

Schema description coverage is 0% and the claims parameter is just a generic object array, so the description carries the full burden—and it delivers. It thoroughly documents the three claim kinds, all allowed fields, defaults, caps, matching rules, and required field combinations, adding enormous meaning beyond the bare 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 opens with a specific verb and resource: 'Grade spatial listing claims ... against real routing and places data.' It clearly distinguishes this tool from sibling analysis tools by specifying its exact job—verifying structured spatial claims—and even states that free-text parsing belongs to a separate prompt/process, not this tool.

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?

The description explicitly says the tool consumes already-decomposed structured checks, not free text, and points to the verify_listing_claims prompt for the decomposition step. It also gives practical usage constraints such as max 8 claims and max 5 travel_time claims due to routing cost. It stops short of naming an alternative sibling tool, but the usage context is clear enough.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/chuofringer/placeroot'

If you have feedback or need assistance with the MCP directory API, please join our Discord server