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Glama

Safe-Check (recall + counterfeit)

Server Details

Is it recalled or fake? Recall lookup vs live US gov feeds + transparent counterfeit risk signal.

Status
Healthy
Last Tested
Transport
Streamable HTTP
URL

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Tool DescriptionsA

Average 3.8/5 across 3 of 3 tools scored.

Server CoherenceA
Disambiguation5/5

Each tool has a clearly distinct purpose: counterfeit_risk for counterfeit risk assessment, recall_lookup for product recall checks, and safe_check runs both together. There is no ambiguity or overlap in their functionality.

Naming Consistency5/5

All tool names follow a consistent snake_case pattern with descriptive verb-noun combinations (counterfeit_risk, recall_lookup, safe_check). The naming is clear and predictable.

Tool Count5/5

With 3 tools, the server is well-scoped for its domain of product safety checking. Each tool earns its place, covering counterfeit risk, recall lookup, and a combined operation without being too few or excessive.

Completeness5/5

The tool surface covers the core safety checks: counterfeit risk and recall lookup, plus a combined call for convenience. There are no obvious gaps for the stated purpose of a product safety screen.

Available Tools

3 tools
counterfeit_riskAInspect

Assess counterfeit RISK for a collectible listing (a risk SIGNAL, never proof of fake). Combines marketplace base-risk + a price-vs-retail-median check when the item is a known collectible niche. Returns a risk level (low/med/high), a score, the signals, and authenticity advice.

ParametersJSON Schema
NameRequiredDescriptionDefault
priceNoOptional: the listed price to compare against the retail median.
queryYesProduct or brand, e.g. 'Funko Batman' or 'LEGO 10307'.
marketplaceNoOptional: where it's listed, e.g. 'aliexpress', 'ebay', 'etsy'.
Behavior4/5

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

With no annotations provided, the description carries the full burden and clearly states the tool outputs a risk level (low/med/high), score, signals, and advice, and that it is a risk signal, not proof. It does not describe any side effects, required permissions, or rate limits, but the behavior is well-scoped and non-destructive.

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 two sentences, front-loads the primary purpose and caveat, and efficiently covers the tool's logic and return values. Every sentence adds value with no redundancy.

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 3-parameter tool with no output schema, the description explains the return values (risk level, score, signals, advice) and the condition for the price check. It is nearly complete, though it does not mention error conditions or bounds for the risk levels.

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?

Schema description coverage is 100%, so the schema already documents each parameter. The description adds no additional semantic meaning beyond the schema; it restates the price parameter's purpose. The baseline of 3 is appropriate.

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 uses a specific verb ('assess') and resource ('counterfeit RISK for a collectible listing') along with a clarifying caveat ('a risk SIGNAL, never proof of fake'). It distinguishes itself from sibling tools by detailing its unique combination of signals (marketplace base-risk and price-vs-retail-median check).

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 usage when the item is a known collectible niche, but it does not explicitly state when to use this tool versus the sibling tools (recall_lookup, safe_check) or provide exclusion criteria. There is no guidance on when not to use it.

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

recall_lookupAInspect

Look up active US product recalls for a product or brand against live government feeds (CPSC/FDA/NHTSA-style aggregate). Returns matching recalls with the official agency source link and last-updated date. Use to check if something is recalled before buying/using it.

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYesProduct name or brand, e.g. 'Peloton bike' or 'stroller'.
Behavior3/5

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

No annotations provided, so description carries full burden. It states returns include agency source link and date, and that it uses live feeds. Does not mention rate limits, authentication, or error handling, but provides core behavior.

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 efficient sentences, front-loaded with purpose and outcome. No unnecessary words.

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 simple tool with one parameter and no output schema, the description covers purpose, scope (US, active, government feeds), and return content. Lacks mention of edge cases like no results, but sufficient for most uses.

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?

Schema description coverage is 100% for the single parameter, and the description adds value with examples ('Peloton bike' or 'stroller') and clarifies it's for product or brand.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it looks up active US product recalls from government feeds, specifying verb and resource. It does not explicitly distinguish from sibling tools (counterfeit_risk, safe_check) but the domain is clear.

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?

Explicit usage context given: 'Use to check if something is recalled before buying/using it.' No exclusions or alternatives mentioned, but the use case is clear.

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

safe_checkAInspect

Run both a recall lookup and a counterfeit-risk check in one call. Best general-purpose product-safety screen.

ParametersJSON Schema
NameRequiredDescriptionDefault
priceNo
queryYes
marketplaceNo
Behavior3/5

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

No annotations provided, so description must cover behavioral traits. It discloses that the tool runs two checks in one call. However, it does not state read-only/destructive nature, auth needs, or side effects. Adequate but not detailed.

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?

Single sentence with no wasted words, front-loaded action, and clear purpose. Highly concise and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 3 parameters, no output schema, and no annotations, the brief description is insufficient. Lacks parameter explanations, return value details, and usage context. Agent cannot fully utilize the tool.

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

Parameters1/5

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

Schema description coverage is 0%, and the description provides no information about parameters. It does not mention price, marketplace, or query purpose, leaving the agent to guess. No value added beyond bare schema.

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?

Description clearly states it performs both a recall lookup and counterfeit-risk check in one call, distinguishing it from siblings that are single-purpose tools. Verb is specific and resource is product-safety screen.

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?

Description says 'Best general-purpose product-safety screen,' implying use for general safety checks. Sibling tools are named (counterfeit_risk, recall_lookup), suggesting alternatives for specific checks. Lacks explicit when-not conditions.

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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