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scout.get_seller_signals

Retrieve Flika's proprietary seller-intent signals: probate filings, distressed properties, expired listings, FSBO intercepts (SC, GA, FL). Returns scored, deduplicated leads with property address + executor contact. Requires a Flika MCP API key with 'seller_signals' scope. Partner brokerages licensed in the lead's state receive these at no per-lead fee (referral fee applies on close).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax leads to return (1-50, default 20).
stateNoFilter by state.
countyNoFilter by county slug (e.g. 'greenville-sc').
min_scoreNoMinimum Claude-assigned score 0-100 (default 0).
since_daysNoHow many days back to look (1-90, default 7).
signal_typesNoWhich signal types to include (default: all).

TDQS

A3.9/5.0
Behavior4/5

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

Without annotations, the description carries full burden. It discloses that returns are 'scored, deduplicated leads with property address + executor contact', mentions API key and scope requirements, and licensing terms. This provides significant behavioral context beyond a simple read.

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 two sentences, front-loaded with purpose, and includes necessary details. It is concise but could be slightly more structured (e.g., separating business terms). No superfluous content.

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?

Given 6 parameters and no output schema, the description explains return value format (scored, deduplicated leads with contact info) and covers licensing. It is complete enough for an agent to understand what the tool produces, though error handling is not mentioned.

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 each parameter already has a description. The tool description adds overall context but does not elaborate on parameter usage beyond what the schema provides. Baseline score of 3 is appropriate.

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 'Retrieve Flika's proprietary seller-intent signals' with specific signal types and geographic scope, distinguishing it from sibling tools that focus on agents, brokerages, or listings.

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 description implies usage for finding seller leads but does not explicitly state when to use this tool versus alternatives or provide exclusions. No sibling tools offer similar functionality, so context is adequate but lacks explicit guidance.

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

A4.2/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose, from agent profiles and comparisons to market data and lead management. Overlaps like find_agent vs find_public_agent are explicitly differentiated by live vs directory status.

Naming Consistency4/5

All tools use snake_case and the 'scout.' prefix, but they mix verb_noun (e.g., compare_agents, search_listings) and noun_noun (e.g., agent_profile, coverage) patterns. However, the naming remains predictable and readable overall.

Tool Count5/5

With 18 tools, the server covers agent discovery, brokerage info, market data, listings, lead management, referrals, and licensing—well-scoped for a real estate assistant without redundancy.

Completeness5/5

The tool set covers all key workflows: agent and brokerage search, market insights, school data, listing search, lead generation and purchase, referral management, and license verification, with no obvious gaps for its domain.