Search AI capabilities across AWS Marketplace and the Official MCP Registry.
Each tool targets a distinct operation: searching, retrieving a specific item, comparing, finding alternatives, summarizing results, building reports, and checking status. There is no meaningful overlap between tool purposes.
Most tools follow a verb_noun pattern (build_, compare_, find_, get_, search_), but market_category_summary and market_status use a noun-first style. The pattern is largely consistent with minor deviations.
Seven tools is well-scoped for a market intelligence server. Each tool covers a distinct capability without redundancy or bloat.
The surface covers the core workflow: search, retrieve, compare, find alternatives, summarize, report, and status. It lacks explicit CRUD operations, but this is a read/analysis-focused domain, so the gaps are minor.
Build a source-backed decision report for one to eight catalog items, including market presence and evidence gaps.
| Name | Required | Description | Default |
|---|---|---|---|
| ids | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry safety and behavior information. It does not state whether the operation is read-only, whether it calls external sources, what the report format is, or if it has side effects. The only behavioral hints are 'source-backed' and 'evidence gaps', which shed little light on outcome.
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?
Single sentence with no filler; verb, object, input bounds, and key content are all included. The phrase 'including market presence and evidence gaps' is valuable but not overdone.
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?
For a tool with one required parameter and no output schema, the description is shorter than ideal. It leaves an agent unclear about the return structure (string, JSON, file), potential delays, and failure behavior. Still, a basic call is possible because the tool name and description establish a clear deliverable.
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?
The schema has no descriptions, so the description must interpret the 'ids' property. It correctly conveys that the parameter refers to catalog items and that 1–8 are accepted. However, it never names the property or specifies what kind of identifiers are expected, and duplicate handling is unaddressed.
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's function: building a 'source-backed decision report' for 1–8 catalog items, with scope and content. It distinguishes itself from 'compare_market_items' and 'market_category_summary' through the report output emphasis, though it does not explicitly contrast with them.
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?
No guidance is given about when to choose this tool over the listed alternatives, such as compare_market_items or market_category_summary. The only condition is the item-count range, which is a constraint rather than a selection rule. An agent must infer that a 'decision report' is needed, so this dimension is weak.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Compare two to eight rich xOmniMarket records without inventing cross-source score equivalence.
| Name | Required | Description | Default |
|---|---|---|---|
| ids | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It discloses a key behavioral constraint: the tool does not invent cross-source score equivalence, which tells the agent not to expect or create a unified score. It does not mention return format or failure modes, but the core behavior is meaningfully described.
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?
One sentence with no filler; the action verb is front-loaded and the behavioral caveat is appended. Every part contributes to understanding the tool.
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?
The description captures the tool's core function and its main caveat, which is sufficient for a simple single-parameter tool without an output schema. It is missing explicit usage alternatives relative to siblings, but the missing information is minor given the tool's simplicity.
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?
The only parameter, 'ids', is given semantic meaning by the phrase 'rich xOmniMarket records' and the count range 'two to eight' matches the schema constraints. Since schema description coverage is 0%, the description fully compensates by explaining what ids represent and how many to provide.
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 states the specific verb 'compare', the resource 'rich xOmniMarket records', and the count range 'two to eight'. The added constraint 'without inventing cross-source score equivalence' clarifies the tool's precise role, distinguishing it from siblings like get_market_item or search_market.
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 clearly implies the tool is for comparing a set of records, but does not explicitly mention alternatives or give exclusion conditions. The phrase 'two to eight' sets a clear precondition for use, yet there is no guidance about when to choose this over find_alternatives or build_decision_report.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Find evidence-backed similarity alternatives to a rich catalog item. Similarity does not imply product identity or interchangeability.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| limit | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It adds one genuine behavioral trait — the warning that 'similarity does not imply product identity or interchangeability' — which meaningfully shapes how the agent should interpret results. However, it omits other behavioral context like output shape, failure modes, or what 'evidence-backed' means in practice.
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 short sentences with zero waste; the action verb and resource are front-loaded and the caveat earns its place in the second sentence. The description is appropriately sized for what it covers.
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 no annotations, no output schema, and 0% parameter coverage, the description leaves substantial gaps: what kind of ID is expected, what the returned alternatives look like, how 'rich' is defined, and what happens when no alternatives exist. An agent could call the tool, but would struggle to interpret or validate the result.
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 0%, so the description should compensate for the two undocumented parameters, but it says nothing about them. The 'id' parameter's semantics (which catalog item, what kind of identifier) are left entirely to inference, and 'limit' only gains meaning from its schema constraints.
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 states a specific verb ('Find') and resource ('evidence-backed similarity alternatives to a rich catalog item'), making the core purpose clear. It is distinguishable from siblings like get_market_item and search_market, though it never names them or explicitly contrasts itself.
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?
No guidance is given on when to use this tool versus siblings such as search_market, compare_market_items, or get_market_item. The caveat about similarity not implying interchangeability is a semantic warning, not usage direction, so an agent gets no help choosing between alternatives for the same task.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return the rich source-backed xOmniMarket record for one market entity id, including confirmed AWS/MCP presence.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the record is 'rich source-backed' with 'confirmed AWS/MCP presence', but does not disclose read-only behavior, potential errors, authentication needs, or response structure. Lacks sufficient transparency for a tool with zero annotation context.
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 a single sentence that efficiently delivers the core purpose and key distinguishing features. No wasted words, and the most important information is front-loaded.
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?
The tool is simple with one parameter and no output schema. The description gives enough to understand basic usage, but lacks details on return format, edge cases, or how it relates to siblings. Adequate for a simple get-by-id tool, but could include more behavioral context.
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?
The schema has a single 'id' parameter with no description (0% coverage). The description compensates by clarifying that the id is a 'market entity id', giving it semantic meaning beyond the bare schema definition. That is meaningful addition.
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 states a specific verb ('Return') and resource ('xOmniMarket record for one market entity id'), and adds distinguishing details ('rich source-backed', 'confirmed AWS/MCP presence'). It clearly differentiates from siblings like search_market, which implies querying, by focusing on retrieving a single record by ID.
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 implies the tool is for fetching a specific record when an entity ID is known, but it does not explicitly state when to prefer it over alternatives such as search_market or compare_market_items. The usage context is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Summarize the current bounded xOmniMarket search results for a category or capability query. This is a search-result summary, not an exhaustive market census.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | ||
| source | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the behavioral disclosure. It discloses that this is a search-result summary and not a full market census, which sets expectations about scope. However, it doesn't mention whether it mutates anything, requires prior search state, or describes output behavior, so it is only partially 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?
The description is only two sentences, front-loaded with the core purpose and followed by a clarifying limitation. Every word adds value and there is no repetition or filler.
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?
The tool is simple, but the description omits parameter semantics and return value expectations (no output schema). Since the description does not explain how to use the parameters or what a summary looks like, it is incomplete for an agent that needs to invoke it correctly.
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?
The input schema has 0% description coverage and the description does not mention either parameter ('text' or 'source'). It fails to explain what 'text' should contain (e.g., the category/capability query) or what values 'source' selects between. With no parameter guidance in the description, an agent has to infer meaning purely from the schema enum.
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 states a specific verb ('Summarize') and a clear resource ('current bounded xOmniMarket search results'), and clarifies scope with 'not an exhaustive market census'. It distinguishes itself from siblings like search_market by indicating this tool works on existing bounded results rather than performing a new search.
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 implies this tool is used when there are current bounded xOmniMarket search results to summarize, but it does not explicitly state when to use it instead of alternatives like search_market or compare_market_items. The exclusion of 'exhaustive market census' gives a slight hint, but no direct alternative routing is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return xOmniMarket source population and freshness status.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the burden. 'Return' suggests a read-only status operation, but it does not specify behavior such as whether data is cached, whether it triggers refresh, or what 'freshness' means. Acceptable for a simple status tool, but minimal.
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 one concise sentence with no filler words. It front-loads the action and directly names the resource and the two status dimensions, making it easy to parse.
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?
For a simple zero-parameter status tool, the description is adequate but not complete. It names what status covers (population and freshness) but does not describe return format, update semantics, or potential error conditions, especially given the lack of an output schema.
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?
The tool has zero parameters and an empty input schema, so parameter documentation is irrelevant. Baseline for zero-parameter tools is 4, and the description does not need to compensate for missing parameter schema.
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 the tool returns status information about xOmniMarket source population and freshness. The verb 'return' is specific enough, but it does not explicitly contrast with sibling search_market, leaving some differentiation to inference.
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?
No guidance is provided about when to use this tool instead of search_market or when not to use it. The intended context is implied by the name and description, but there is no explicit usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search qualifying AI capabilities across AWS Marketplace and the Official MCP Registry. Returns both sources by default.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | ||
| source | No | ||
| perSource | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly states the tool searches two sources and returns results from both by default. It does not disclose return format, pagination, rate limits, or whether search is case-sensitive, but for a straightforward search tool this is reasonable. No contradictions with annotations since none exist.
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 only two short sentences, free of filler or repetition. It front-loads the core purpose and then adds the critical detail about default dual-source behavior. No wasted words.
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 has 3 parameters, no output schema, and no annotations, the description provides the essential purpose and default behavior. It does not explain return values (no output schema exists, so the description could be more helpful there), but for a search tool with enum-based filtering, this is largely complete. The sibling context adds marginal completeness.
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?
Despite having 0% schema description coverage, the description adds meaning beyond the input schema by stating the tool searches for 'qualifying AI capabilities' and notes the default behavior of returning results from both sources. This implies meaning for the 'text' and 'source' parameters. However, it does not explicitly describe the 'perSource' parameter meaning beyond what is already in the schema (integer, max 25, min 1).
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 uses a specific verb 'Search' and clearly identifies the resource as 'qualifying AI capabilities across AWS Marketplace and the Official MCP Registry'. It explicitly states the default behavior of returning results from both sources, which distinguishes it from siblings like 'market_status' that presumably checks service status rather than performs searches.
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 implicitly states that the tool searches both sources by default, and the 'source' parameter allows narrowing to either 'aws' or 'mcp'. However, it provides no guidance on when to use 'market_status' instead, nor does it explicitly exclude scenarios where this tool is inappropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
build_decision_reportcompare_market_itemsfind_alternativesget_market_itemmarket_category_summarymarket_statussearch_marketClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
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