Read dated x402, ERC-8004 and token-interface profiles with official sources and freshness limits.
Scored across 3 tools
search and fetch form a clean find-then-retrieve pair, but read_protocol_profiles blurs the boundary because its own description says profiles can be retrieved 'with fetch' as well, making it unclear when to use fetch versus read_protocol_profiles. The generic name 'fetch' further obscures which resource types it covers.
Two tools use bare verbs (fetch, search) while one uses a verb_noun pattern (read_protocol_profiles). All lowercase snake_case is consistent, but the verb conventions are mixed, which is readable yet not a predictable pattern.
Three tools is on the lean side but fitting for a small read-only reference server covering search, retrieval and a protocol ledger. The find/list/retrieve surface is adequately scoped rather than padded.
For a read-only reference domain, search (with empty-query listing), fetch by ID and protocol profile retrieval cover the core lifecycle with no create/update needs. Minor gap: there is no explicit listing tool for tool references beyond search's empty-query fallback.
Retrieve a public tool reference by the ID returned from search. Contains methodology, limits, official source links and fictional worked examples; no user records. Cite the returned canonical URL.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes |
| Name | Required | Description |
|---|---|---|
| id | Yes | |
| url | Yes | |
| text | Yes | |
| title | Yes | |
| metadata | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and a closed world, so the safety profile is covered. The description adds genuinely new context: the payload contents (methodology, limits, official sources, fictional worked examples), the absence of user records, and the citation obligation for the canonical URL.
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 sentences, front-loaded with the action, then the payload and scope, closing with the actionable citation instruction. No filler and every clause carries information.
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?
An output schema exists, so return-format details are not needed, yet the description still summarizes the returned content and its fictional nature. Combined with the scope caveat and citation rule, an agent has what it needs; only the enum's meaning and error behavior remain unaddressed.
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% and the single enum parameter has only the value 'protocol'. The description supplies the important semantic — that the ID comes from a prior search call — but gives no guidance on what the enum value represents or what to do if the ID is stale or unknown.
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?
States a specific verb and resource ('Retrieve a public tool reference') and ties it to the search workflow via 'by the ID returned from search', which distinguishes it from the search sibling. The naming drifts between 'tool reference' here and 'Web3 method' in the title, so the resource is slightly ambiguous.
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?
It implies the correct sequence by requiring the ID from search, which is useful chaining guidance. However, it never states explicitly when to call this instead of read_protocol_profiles, and offers no exclusion beyond the mild 'no user records' scope note.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Protocol Ledger is a free, dated reference for five payment, agent-identity and token interfaces. Each record preserves its official specification, review date and interpretation limits. Filter the same snapshot in the browser or retrieve it through the JSON API. Five initial profiles; no market prices, exhaustive schema coverage, real-time protocol monitoring or paid endpoint. Retrieve protocol with fetch or read its example resource to obtain exact inputs. Parameters are processed remotely without application persistence.
| Name | Required | Description | Default |
|---|---|---|---|
| asOf | Yes | Review date (UTC) (preserve source text; decimal amounts must stay strings) | |
| status | Yes | Status (preserve source text; decimal amounts must stay strings) | |
| purpose | Yes | Purpose (preserve source text; decimal amounts must stay strings) | |
| maxAgeDays | Yes | Maximum evidence age (days) |
| Name | Required | Description |
|---|---|---|
| report | Yes | |
| toolId | Yes | |
| version | Yes | |
| citation | Yes | |
| revision | Yes | |
| processing | Yes | |
| limitations | Yes | |
| evidenceStatus | Yes | |
| officialReferences | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish readOnly/idempotent/non-destructive behavior; the description adds useful context beyond them: 'Parameters are processed remotely without application persistence,' the snapshot/dated-review semantics, and the 'Five initial profiles' scope limit. No contradiction with annotations.
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 opening sentence is informative and front-loaded, but the description becomes padded with a browser-vs-JSON-API comment, a redundant 'Five initial profiles' clause, and the vague 'Retrieve protocol with fetch or read its example resource' sentence. It is serviceable but not crisp.
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 strong annotations, complete input schema, and existing output schema, the description provides enough operational context: it describes the data scope, honors read-only semantics, and discloses non-persistence. The main remaining gap is not explicitly saying what the returned profiles are for, but that is largely covered by the tool name and 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 input schema has 100% description coverage and already explains all four parameters, including enums and the 'preserve source text' instruction. The tool description adds no meaningful parameter-level meaning beyond the schema, so the baseline of 3 is appropriate.
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 frames the tool as a 'free, dated reference' for payment, agent-identity, and token interfaces and states its limits ('no market prices, ... real-time protocol monitoring or paid endpoint'). It stops short of a crisp 'returns protocol profiles filtered by status/purpose/asOf' statement and does not differentiate itself from sibling read/search tools by name.
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 'dated reference' framing plus explicit exclusions ('no market prices, exhaustive schema coverage, real-time protocol monitoring or paid endpoint') gives an agent usable guidance about when not to pick this tool. It also points to fetch/example resources for exact inputs. However, it never explicitly names sibling alternatives or states a clear 'use this when...' condition.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search this server’s public AI/Web3 tools and citation pages. English and Chinese names supported. Empty query lists the available worksheets.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
| Name | Required | Description |
|---|---|---|
| results | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish read-only, idempotent, non-destructive behavior, and the description adds valuable behavioral context: bilingual (English and Chinese) name support, public scope, and the empty-query listing behavior. These details go beyond what annotations or schema provide 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 clean sentences with no filler. The primary action is front-loaded, and the supporting usage details are kept minimal 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 single-parameter search tool with annotations and an output schema, the description is complete: it defines the search scope, supported query forms, and the empty-query behavior. No essential information for invoking the tool correctly 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 coverage is 0%, so the description carries the burden of explaining the query parameter. It clarifies that queries are names, that English and Chinese are accepted, and that an empty query has special meaning. It does not fully specify matching behavior (e.g., exact vs partial), but it compensates well for the schema gap.
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 ('Search') and resource ('this server’s public AI/Web3 tools and citation pages'), making the tool’s function immediately clear. It is distinct from all sibling tools, which focus on checking permissions, comparing costs, or reading profiles rather than searching a corpus. The title and description align well.
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 indicates when to use the tool: when searching for AI/Web3 tools or citation pages on this server. The note about empty query listing available worksheets provides a concrete usage scenario. It does not explicitly name alternatives or exclusion conditions, so it misses the top score.
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.
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