Skip to main content
Glama
mikki321

night-margin-mcp

by mikki321

Check gap night fill (FILL/SKIP)

gap_night_check

Evaluates whether filling a vacant night is profitable by computing a floor price based on costs and minimum margin, then comparing the candidate price. Returns fill or skip verdict with net after turnover costs.

Instructions

Checks whether filling a single gap night is worth it: computes the floor price (turnover cost + travel + minimum margin MIN_MARGIN, adjustable with the risk preset) from the median of the property's actual cost rows and compares the candidate price against it → FILL if price ≥ floor, otherwise SKIP. The verdict reports both the floor clearance and the actual net after turnover costs. If the date is already booked, reports which booking covers it. Read-only — never changes any prices.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateYesNight to check, YYYY-MM-DD
riskNoRisk preset for the floor's minimum margin (Wheelhouse's own CON/REC/AGG language): conservative doubles MIN_MARGIN, recommended keeps it as configured (default), aggressive uses 40% of it.
property_idYesProperty identifier in the reservation data (property_id)
candidate_priceNoCandidate price €/night — compared against the floor price; without it only the floor + guidance is shown
Behavior5/5

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

With no annotations, the description fully explains the algorithm: floor price computation from median cost rows, adjustable margin via risk preset, comparison with candidate price, and the verdict. It also mentions behavior for already-booked dates and confirms no state changes. No contradictions.

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 coherent paragraph, front-loaded with purpose, then explaining the algorithm and verdict. Every sentence adds necessary information, with no redundancy or fluff.

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 no output schema, the description adequately explains return values: floor clearance, net after turnover costs, and booking info if applicable. All four parameters are covered, and the tool's behavior is fully described for its complexity.

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

Parameters4/5

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

All parameters are described in the schema (100% coverage). The description adds behavioral meaning: how candidate_price is optional and used, how risk preset adjusts margin, and the role of property_id and date in computing floor price. This adds value beyond schema definitions.

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 the tool's purpose: checking whether filling a single gap night is worth it, with a specific verb ('Checks') and resource ('gap night'). It distinguishes from sibling tools by focusing on a single night assessment rather than portfolio analysis or strategy proposals.

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 when to use (when deciding about a gap night) and notes it is read-only, but does not explicitly state when not to use or compare with sibling tools like propose_decisions or apply_decision. The usage context is implied rather than prescribed.

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

Install Server

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/mikki321/night-margin-mcp'

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