list_shadow_aiList AI tools from the registry, optionally filtered by category. Returns name, domain, category, and risk band. Covers the free top 100.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results (default 25, max 100). | |
| category | No | Optional category filter (e.g. 'coding', 'chatbot', 'meeting_transcription'). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false, so the read-only nature is established. The description adds useful context beyond annotations by clarifying the result scope ('Covers the free top 100') and the output fields, which is valuable given no output schema.
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 extremely concise: two sentences with no fluff. It front-loads the primary action and includes relevant output details and scope in the second sentence.
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 list tool with complete schema coverage, annotations, and no output schema, the description provides enough context: what is returned, optional filtering, and scope. It could be slightly more explicit about ordering or pagination, but the current description is sufficiently complete for selection and 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 input schema has 100% parameter coverage with descriptions for both limit and category. The description reiterates category filtering but does not add extra semantic meaning beyond the schema, such as behavior of the limit default or category examples.
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 purpose: listing AI tools from the registry with optional category filtering. It specifies the returned fields (name, domain, category, risk band) and scope (free top 100), which distinguishes it from sibling tools like lookup_ai_tool_risk that target specific lookups.
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 when to use it: when you need a list of AI tools from the registry, optionally filtered by category. However, it does not explicitly mention alternatives or exclusion cases, such as using lookup_ai_tool_risk for a specific tool or get_top_risky_ai for risk-focused ranking.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool serves a clearly distinct purpose: check_domain_against_registry verifies domains, get_top_risky_ai returns ranked risk, list_shadow_ai provides a filterable list, and lookup_ai_tool_risk retrieves detailed info by name/vendor/domain. No two tools overlap in a way that would cause selection confusion.
All tool names follow a consistent verb_noun pattern using snake_case: check_, get_, list_, lookup_. The verbs accurately describe each action and the pattern is uniform across the set.
With 4 tools, the server is well-scoped for a read-only registry. Each tool covers a distinct query type without being overly redundant or too sparse. This is an appropriate size for the intended purpose.
The server covers the core operations: domain checking, listing, top-risk ranking, and detailed lookup. A minor gap is the lack of a way to discover available categories for filtering, since list_shadow_ai accepts a category parameter but no tool enumerates them. Overall, the surface is nearly complete for a registry lookup service.