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Glama

cost-seg-smart

Server Details

Cost segregation study pricing and Year-1 depreciation/tax-savings estimates for US properties.

Status
Healthy
Last Tested
Transport
Streamable HTTP
URL

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Tool DescriptionsA

Average 4.6/5 across 2 of 2 tools scored.

Server CoherenceA
Disambiguation5/5

The two tools serve entirely different purposes: one provides a quote, the other generates a payment link. There is no ambiguity between them.

Naming Consistency5/5

Both tools follow the exact pattern 'get_cost_seg_<action>', using consistent snake_case and meaningful suffixes.

Tool Count4/5

With only 2 tools, the server is minimal but appropriately scoped for quoting and purchasing a cost segregation study. It could be expanded slightly (e.g., status check), but the count is reasonable.

Completeness3/5

The tools cover the essential tasks (quote and initiate purchase), but there is no way to confirm payment status or retrieve the study after purchase, leaving a notable gap.

Available Tools

2 tools
get_cost_seg_quoteA
Read-onlyIdempotent
Inspect

Quote a CPA-ready cost segregation study for a US real estate property. Returns the study cost in USD, estimated Year-1 accelerated depreciation, and (when a tax bracket is provided) Year-1 tax savings and ROI on the study fee. Pure tier-matrix lookup — no engine run, no charge to the buyer, safe to call repeatedly. Use this before generating a payment link so you can confirm the price with the buyer. Does not provide tax advice.

ParametersJSON Schema
NameRequiredDescriptionDefault
tax_bracketNoOptional. Buyer's federal marginal tax bracket. Accepts decimal form (0.0-0.6, e.g. 0.32 for 32%) OR whole-number percent (0-60). When provided, response includes tax_savings_year_one and roi_multiple. When omitted, response only includes the deduction estimate.
property_typeYesProperty type identifier. Determines the pricing tier and the default Year-1 reclassification percentage. Residential types (sfr, str, condo, condo_str, adu) reclassify ~22-30%; small multifamily (duplex/triplex/fourplex) ~27%; commercial varies by subtype (~18-30%).
purchase_priceYesProperty purchase price in US dollars. Minimum $50,000. The pricing tier is computed from this value. Properties >= $25M fall in the institutional custom-quote tier.

Output Schema

ParametersJSON Schema
NameRequiredDescription
currencyYesAlways 'USD' — Cost Seg Smart is US-only.
next_stepYesHuman-readable instruction for the agent's next call.
disclaimerYesStandard estimate disclaimer to show the buyer.
study_costNoStudy cost in USD. Null for the institutional custom-quote tier (price >= $25M) — see study_cost_tier.
roi_multipleNoYear-1 return on the study fee = tax_savings_year_one / study_cost, rounded to integer. Null when tax_bracket was not provided or study_cost is null.
property_typeYesEcho of the requested property_type.
purchase_priceYesEcho of the requested purchase_price (USD).
study_cost_tierYes'fixed_price' = study_cost is a real USD amount. 'institutional_custom' = property is in the $25M+ tier; route the buyer to support@costsegsmart.com.
property_type_labelYesHuman-readable label (e.g. 'Short-Term Rental').
tax_savings_year_oneNoEstimated Year-1 federal tax savings in USD = deduction_estimate_year_one × tax_bracket. Null when tax_bracket was not provided.
deduction_estimate_year_oneYesEstimated Year-1 accelerated depreciation in USD, computed as purchase_price × (1 - 0.18 land) × reclass_pct[property_type]. Assumes 100% bonus depreciation per OBBBA §168(k) (2025+).
Behavior5/5

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

Discloses that it's a pure tier-matrix lookup with no engine run, no charge, and safe to call repeatedly, complementing the readOnlyHint and idempotentHint annotations.

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?

Two sentences front-loaded with purpose, no wasted words. Every sentence adds value.

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?

Given output schema exists, description doesn't need to explain returns. It covers input semantics, conditions, and relationship to payment link. Fully sufficient for an AI agent.

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?

Adds meaningful context beyond schema: tax_bracket accepts decimal or percent, property_type includes example percentages, purchase_price has minimum and mentions $25M tier. Schema coverage is 100% but description enriches it.

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?

Clearly states it quotes a cost segregation study, returns cost, depreciation, and optionally tax savings. Distinguishes from sibling 'get_cost_seg_payment_link' by noting it's used before generating a payment link.

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?

Explicitly says when to use ('before generating a payment link'), and clarifies it does not provide tax advice or charge the buyer. Safe to call repeatedly, no side effects.

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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