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Rental listing risk

rental_listing_risk
Read-onlyIdempotent

Explainable rental-fraud risk score over listing red-flag signals (deterministic rule engine).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urgency_pressureNoPressure to secure today.
no_in_person_viewingNoNo viewing before payment.
payment_irreversibleNoPaid via crypto/gift-card/wire-only.
price_below_market_pctNoHow far below local market the rent is asked, in percent.
photos_reverse_image_hitNoListing photos found elsewhere (stolen).
contact_moves_offplatformNoPushed off the listing platform.
landlord_abroad_cannot_meetNoLandlord 'abroad', can't meet in person.
identity_docs_requested_upfrontNoFull ID/bank docs demanded upfront.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
bandYes
toolNo
flagsNo
scopeNo
risk_scoreYes
flags_firedNo
recommendationNo

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds useful behavioral context by noting the engine is deterministic and explainable, but it does not describe output details or edge-case behavior. No contradiction with annotations exists.

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?

The description is a single, economical sentence with no filler. It front-loads the key concepts—explainable output, rental fraud, and deterministic rule engine—and earns every word.

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 present and all 8 parameters fully described in the input schema, the description does not need to explain return shape or parameter semantics. It sufficiently conveys tool purpose and core behavioral traits, though it could add a sentence on when this risk score is preferable to related rental tools.

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 description coverage is 100%, so parameters are already fully documented. The description adds the collective framing of these inputs as red-flag signals, which gives semantic context, but it does not explain individual parameters beyond what the schema provides. Baseline 3 is appropriate.

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?

The description clearly states the tool produces an explainable rental-fraud risk score over listing red-flag signals, which identifies the domain, resource, and output. It is specific enough to distinguish itself from generic validation tools, though it does not explicitly contrast itself with the related rental_verdict sibling.

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

Usage Guidelines2/5

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

The description gives no explicit guidance about when to use this tool versus alternatives such as rental_verdict or rent_deposit_guard. It does not state exclusion criteria, prerequisites, or recommended use cases, leaving the agent to infer applicability.

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

A3.8/5.0
Disambiguation5/5

Each tool targets a distinct identifier type or data source: every checksum validation is for a specific standard (IBAN, LEI, VAT, etc.), and the on-chain and rental tools are clearly separate domains. There is no ambiguity between tools; even similar-sounding checks like 'luhn_check' and 'ean13_check' are distinct algorithms with explicit descriptions.

Naming Consistency3/5

Most validation tools follow a 'X_check' pattern (iban_check, swift_bic_check, ein_format_check), but others deviate: 'company_number_format' uses a noun_noun structure, 'block_info' is noun_noun, and 'batch_validate' and 'context_distill' use verbs. While the pattern is not uniform, the names are readable and the convention is understandable, just not fully consistent.

Tool Count2/5

With 28 tools, this server exceeds the typical 3-15 well-scoped range and even the 16-25 heavy range. The server covers multiple unrelated domains (identifier validation, blockchain queries, rental fraud, text processing), which inflates the count. While each tool is individually justified, the overall surface feels overly broad for a single MCP server.

Completeness4/5

For each sub-domain, coverage is strong: identifier validation includes a wide range of international standards, on-chain queries cover balances, activity, and settlement history, and rental tools provide risk, verdict, and deposit guard. Minor gaps exist (e.g., no country-specific tax IDs beyond what's listed, no transaction history for arbitrary tokens), but the visible coverage is comprehensive for the stated purposes.

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