Scalper Price Checker
Server Details
Check if a collectible's price is FAIR/OVER/SCALPED vs the current retail median across shops.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.6/5 across 2 of 2 tools scored.
List niches and price check have clearly distinct purposes: one provides available categories, the other assesses a price against market data. No functional overlap.
Both tools use consistent snake_case verb_noun naming (list_niches, price_check), following a predictable pattern.
With only two tools, the set feels thin for a price-checking service. While it covers the essential query flow, a few more tools (e.g., search by item, compare multiple) would feel more complete.
The tool surface is limited: the agent can list niches and check a single price against a median, but there are no tools to get detailed item information, search, or handle multiple items. Significant gaps for practical use.
Available Tools
2 toolslist_nichesAInspect
List the collectible niches this price checker covers (TCG, LEGO, Funko, keyboards, vinyl, aquarium). Use first to pick a valid 'niche' value for price_check.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description fully covers behavior: it lists niches. No destructive or complex side effects implied. Provides concrete examples, making expected output transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff. Efficiently states purpose, gives examples, and provides usage direction. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and no output schema, description fully covers what the tool does and how to integrate with sibling. No additional context needed for this simple listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters in schema; baseline is 4. Description adds significant value by enumerating example niche values, which helps the agent understand what will be returned.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states tool lists collectible niches for the price checker, with specific examples (TCG, LEGO, Funko, keyboards, vinyl, aquarium). Distinguishes from sibling 'price_check' by indicating this is a preparatory step.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool: 'Use first to pick a valid niche value for price_check.' Provides clear dependency between list_niches and price_check.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
price_checkAInspect
Check whether a price for a collectible is FAIR / OVER / SCALPED vs the current retail median across the shops we poll. Returns the retail min/max/median, the number of shops carrying it, the price multiple, and a verdict. Use this to decide if a listing is overpriced before buying. niche must be one of: tcg (Pokémon & TCG), lego (LEGO sets), funko (Funko Pop), keebs (Mechanical keyboards), vinyl (Vinyl records), aqua (Aquarium livestock).
| Name | Required | Description | Default |
|---|---|---|---|
| niche | Yes | Niche key, e.g. 'tcg', 'lego', 'funko', 'keebs', 'vinyl', 'aqua'. | |
| price | No | Optional: the price you are seeing. If given, the verdict compares against it. | |
| query | Yes | Product name to look up, e.g. 'Charizard V' or 'LEGO 10307'. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the comparison against a retail median, the return fields, and that the price parameter is optional. However, it lacks details on data freshness, latency, or whether the tool writes any state.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and covers key elements without unnecessary words. While it could benefit from list formatting for readability, it remains efficient and front-loaded with the action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity and lack of output schema, the description adequately explains the return data (min/max/median, shop count, multiple, verdict) and usage. It does not mention error handling or missing data scenarios, but it is complete enough for typical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, but the description adds value by enumerating valid niche values, explaining the optional price parameter, and clarifying how the verdict is determined (comparing to given price). This goes beyond the schema definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks a price against a retail median and returns a verdict (FAIR/OVER/SCALPED) along with market data. It distinguishes from sibling tool 'list_niches' by focusing on price evaluation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this to decide if a listing is overpriced before buying' and lists allowed niche values. It does not provide explicit when-not-to-use guidance, but the purpose is clear enough for most scenarios.
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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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
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