fetchFetch one canonical public source returned by search. The response includes citation-ready title, URL, text, and metadata. It never returns user wallet data or wallet credentials.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | A source ID returned by search, such as product or article:article-slug. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds concrete behavioral details: the response includes citation-ready title, URL, text, and metadata, and it never returns wallet data or credentials. This goes beyond the annotations without contradicting them.
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 two economical sentences with no filler. It front-loads the core action and scope, then adds return-value context and a privacy guarantee. Every clause 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?
For a single-parameter, read-only, idempotent tool with no output schema, the description is complete enough. It explains where IDs come from, what the response contains, and what the tool will never return. No critical operational detail is missing.
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%, and the schema already explains that id is a source ID returned by search with format examples like 'product or article:article-slug'. The description adds no further parameter-level meaning, so the baseline score of 3 applies.
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 and resource: 'Fetch one canonical public source returned by search.' It clearly distinguishes itself from sibling getters like get_article and get_product by emphasizing it is the generic fetch for search results, not a typed accessor.
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 gives clear usage context: use it for source IDs returned by search. It also explicitly warns that it never returns user wallet data or credentials, which is useful for routing agents away from misuse. However, it doesn't name sibling alternatives or state when one should prefer get_article or get_product.
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.
Most tools target distinct resource types (product, security, features, articles, networks, release, screens, entry points), with get_/list_ pairs clearly separating single-item retrieval from collection listing. The only mild ambiguity is between get_app_screen and list_app_entry_points, since both describe UI navigation surfaces, though their descriptions keep screen semantics vs entry-point catalogs separate.
The dominant get_<singular> and list_<plural> pattern is clear and predictable for 10 of 12 tools. 'search' and 'fetch' break the noun-oriented pattern and are less descriptive of their distinct roles, but they are common enough verbs that the overall set remains readable.
With 12 tools, the server is well-scoped for a wallet knowledge base: each get tool corresponds to a distinct knowledge category and list tools cover discoverability. No tool feels redundant, and the count is squarely in the appropriate range.
The surface covers the major knowledge domains an agent needs: product identity, security model, features, articles, supported networks, release info, app screens, and entry points, plus search/fetch for open-ended lookup. Minor asymmetries exist (e.g., get_app_screen has no listing counterpart, and list_app_entry_points has no single-item get), but these are workable through search.