Decision Support Network helps humans and AI agents discover verified decision-support tools for spe
Find relevant CCA Decision Support Assets for a given decision query
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Natural language description of the decision | |
| audience | No | Intended audience (optional) | |
| category | No | Category filter (optional) | |
| geography | No | Geographic context (optional) | |
| max_results | No | Maximum results (default: 5) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of explaining the tool's behavior. It only restates the search intent and does not disclose whether results are ranked, how relevance is determined, whether the operation is read-only, or any limitations. There is no contradiction, but there is also little behavioral disclosure.
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, front-loaded sentence with no filler or redundant phrasing. Every word contributes to conveying the tool's core purpose.
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 input schema covers all parameter meaning, and the tool's search intent is understandable. However, with no output schema and no annotations, the description does not describe return format, ranking, or how filters affect results, leaving a minimally viable but not fully complete picture.
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 already provides descriptions for all five parameters, so the baseline is 3. The description adds little beyond echoing the query concept and does not clarify filter combination, default behavior, or result limits beyond what the schema already states.
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 ('Find'), a resource ('CCA Decision Support Assets'), and the input context ('for a given decision query'). It is clear and suggests a search/retrieval behavior distinct from listing categories or getting details, though it does not explicitly name or contrast the sibling tools.
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?
Usage is implied rather than explicit: the tool should be used when there is a natural-language decision query and relevant assets are needed. The description does not mention when not to use it or point toward get_decision_tool_details or list_decision_support_categories as alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get full details of a specific Decision Support Asset by slug
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | The DSA slug identifier |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says 'Get full details' and does not explain the response format, whether the result includes nested objects, error behavior, permissions, or any limitations. The read-only nature is implied by 'Get' but not substantively disclosed.
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, front-loaded sentence with no filler. Every word contributes: 'Get' states the action, 'full details' states the scope, 'specific Decision Support Asset' states the resource, and 'by slug' states the input mechanism.
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 one-parameter lookup tool, this is adequate but not complete. With no output schema and no annotations, the vague phrase 'full details' leaves the agent guessing what fields or structure to expect. Missing return-format and edge-case guidance lowers the score, though the tool is simple enough that the gap is not severe.
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 already defines the slug parameter with 100% coverage, so the description does not need to add much. The description reaffirms that the slug identifies the specific DSA, but it does not add format requirements, examples, or additional meaning beyond the 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?
The description states a specific action ('Get'), a clear resource ('full details of a specific Decision Support Asset'), and the key identifier ('by slug'). This distinguishes it from sibling tools like find_decision_support_tool (search-oriented) and list_decision_support_categories (category-oriented) by making clear this is a direct, slug-based detail lookup.
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 phrase 'by slug' gives clear context: use this tool when you already have a specific DSA slug and need full details. It does not explicitly name alternatives or state when not to use it, but the slug-based specificity implies the boundary against searching or listing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List all available decision support categories with DSA counts
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full behavioral burden. It discloses scope ('all available') and one output trait ('DSA counts'), but does not explicitly state it is read-only/side-effect-free, nor does it describe response shape, ordering, or limits. This is adequate only for a simple zero-parameter list tool.
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 focused sentence with no wasted words. The action and target resource are front-loaded, and the additional output detail ('with DSA counts') is concise and relevant.
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 parameterless listing tool with no output schema or annotations, the description provides enough information to invoke it correctly. It could be slightly richer by noting how the returned categories relate to get_decision_tool_details, but that connection is not essential for correct invocation.
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, so there is nothing for the description to clarify about inputs. The 100% schema coverage with an empty properties object is inherently complete, and the baseline for zero parameters is 4.
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 ('List') with a clear resource ('decision support categories') and states the included output ('with DSA counts'). It distinguishes well from the sibling tools, which find specific tools or get details rather than enumerating categories.
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 enumerating all available categories, but it gives no explicit guidance about when to prefer it over find_decision_support_tool or get_decision_tool_details. There are no exclusions or alternative routing hints.
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.
find_decision_support_toolget_decision_tool_detailslist_decision_support_categoriesClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
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Each tool has a clearly distinct purpose: find assets, get details by slug, and list categories. There is no overlap or ambiguity in what they do.
All tools follow a verb_noun pattern (find, get, list). Minor inconsistency exists between 'decision_support_tool' and 'decision_tool' in the second tool name, but overall the convention is clear and uniform.
Three tools is slightly minimal but well-scoped for a decision-support catalog lookup service. Each tool covers a distinct need, though the set feels a bit sparse for a 'network'.
The surface covers the core read-only workflow: search for assets, retrieve details, and browse categories. It lacks obvious creation/update/delete operations, but those may be outside the intended scope.
