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Analog-Labs

Firestarter MCP Server

by Analog-Labs

firestarter_drops

List community-funded discount drops for any listing and claim a reserved slot before checkout, first-come, first-served.

Instructions

Community-sponsored drops: a community owner funds a discount on a specific listing for the first N members, sometimes opening it to higher tiers first. Use action 'list' with a listing_id to see any live drops on it — each shows the per-claim discount, how many slots remain, and whether it is still in a tier-gated early-access window. Use action 'claim' with a drop_id to reserve a slot for the buyer before checkout — first-come, first-served, one per member; the reserved discount then applies to that buyer's purchase of the listing. test/live follows the API key's environment.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYes'list' the live drops on a listing, or 'claim' a specific drop_id.
drop_idNoDrop to claim (required for action 'claim').
listing_idNoListing to list drops for (required for action 'list').
Behavior4/5

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

The description adds meaningful behavioral details beyond the minimal annotations: claims are first-come first-served, one per member, and reserved discounts apply to the purchase. It also explains what list shows (discount, slots, tier window) and notes the test/live environment behavior. This goes beyond just saying 'readOnlyHint=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 concise and well-structured. It opens with the core concept, then explains each action in order, and ends with environment behavior. Every sentence contributes value without redundancy or unnecessary detail.

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?

For a tool with two actions and no output schema, the description covers the key aspects: the community-sponsored drop concept, list behavior, claim behavior, and environment. It does not explain edge cases like no drops or error handling, but these are not essential given the tool's simplicity and the schema's clarity.

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?

The input schema already provides high coverage (100%) with descriptions for all parameters. The description reinforces the action-parameter relationship but does not add significant new parameter-level semantics beyond what the schema states. The contextual background on community drops slightly enhances understanding, but the schema carries the main load.

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: handling community-sponsored drops, with specific actions 'list' and 'claim'. It specifies the resource (drops on listings) and differentiates from sibling tools by focusing on community-sponsored drops funded by community owners.

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

Usage Guidelines4/5

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

The description provides clear context on when to use this tool (for community-sponsored drops) and gives explicit instructions for each action. However, it does not explicitly name alternatives or state when not to use the tool, so it falls short of a 5.

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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