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PropContext — Bangalore Real Estate

by app.railway.up.propcontext-production

request_callback

Request an expert callback for a Bangalore real estate project.

Use this when the user wants to speak to an expert but is not ready to visit yet.
Lower commitment than a site visit — just captures name, phone, and preferred call time.

Call this when the user says:
- "I want to know more", "can someone call me", "I'd like a callback"
- "talk to an expert", "get more information", "not ready to visit yet"
- "call me back", "have someone reach out"

Required: rera_number, user_name, user_phone
Optional: preferred_time (e.g. 'Morning', 'Afternoon', 'Evening')
conversation_summary: Summarise in 2-3 bullet points what the buyer is looking for
and any questions they raised — this goes to the expert who calls them back.

Returns confirmation with callback reference ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_nameYes
user_phoneYes
rera_numberYes
preferred_timeNo
conversation_summaryNo

TDQS

A4.8/5.0
Behavior4/5

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

Beyond the annotations, the description discloses that the tool only captures name, phone, and preferred call time, that the callback is lower commitment than a site visit, and that it returns a confirmation with a callback reference ID. This gives useful behavioral context; no contradiction with readOnlyHint=false or destructiveHint=false.

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 well-structured and front-loaded: purpose, usage condition, example triggers, parameter requirements, and return value all appear in a logical order. The utterance list is long but earns its place by removing ambiguity about when to fire the tool.

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?

For a 5-parameter tool with no output schema, the description covers inputs, expected behavior, user intent signals, and the return shape. It also positions the tool against the most relevant sibling, leaving no significant gap for an agent to call 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%, but the description compensates thoroughly: it marks rera_number, user_name, and user_phone as required, gives examples for preferred_time, and explains exactly how to format conversation_summary with bullet points. Each parameter's purpose is made actionable.

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+resource: 'Request an expert callback for a Bangalore real estate project.' It clearly distinguishes itself from the sibling book_site_visit by framing the callback as 'Lower commitment than a site visit,' so an agent can identify when this tool applies.

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?

It explicitly states when to use the tool ('when the user wants to speak to an expert but is not ready to visit yet') and provides concrete example user utterances. It also contrasts with the site-visit alternative, giving the agent clear routing guidance.

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

All PropContext — Bangalore Real Estate toolsInspect
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TDQS

A4.2/5.0
Disambiguation4/5

Most tools have clearly distinct jobs: search vs. details vs. insights vs. booking/callback. The only mild overlap is among the three search tools (structured, fulltext, commute) and between get_project_insights and get_builder_projects on builder credibility, but the descriptions are strong enough to guide correct selection.

Naming Consistency5/5

All tool names follow a predictable verb_noun snake_case pattern: search_* for discovery, get_* for retrieval, and book_/request_ for lead capture. There are no mixed conventions, vague verbs, or inconsistent casing.

Tool Count5/5

10 tools is well-scoped for a real estate assistant: three discovery modes, project detail and insights, builder verification, new launches, personalized shortlist, and two lead-capture actions. Each tool has a clear purpose and the set never feels bloated or thin.

Completeness5/5

The tool surface covers the full buyer journey from discovery and verification to personalized recommendations and conversion (site visit or callback). It also includes builder track-record checks and recent registrations, so there are no obvious dead ends for common real estate queries.

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