authorAuthor lookup (free-text query).
| Name | Required | Description | Default |
|---|---|---|---|
| rows | No | 1-1000 (default 25). | |
| query | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| response | No | Author search results | |
| responseHeader | No | Response metadata |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "query": "Jean Dupont"
+ },
+ {
+ "query": "Smith",
+ "rows": 50
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "description": "Author reference lookup response from HAL API",
+ "properties": {
+ "response": {
+ "description": "Author search results",
+ "properties": {
+ "docs": {
+ "description": "Array of matching author records",
+ "items": {
+ "description": "Author reference object",
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "numFound": {
+ "description": "Total number of matching authors",
+ "type": "integer"
+ },
+ "start": {
+ "description": "Starting offset of results",
+ "type": "integer"
+ }
+ },
+ "type": "object"
+ },
+ "responseHeader": {
+ "description": "Response metadata",
+ "properties": {
+ "QTime": {
+ "description": "Query execution time in ms",
+ "type": "integer"
+ },
+ "params": {
+ "description": "Query parameters echoed back",
+ "type": "object"
+ },
+ "status": {
+ "description": "HTTP status code",
+ "type": "integer"
+ }
+ },
+ "type": "object"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint, idempotentHint, openWorldHint, and non-destructive behavior, so the safety profile is well covered. The description adds the 'free-text query' behavior, which is a useful non-obvious trait not captured in the schema or annotations, though it remains 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 extremely concise and front-loaded, using a short phrase that conveys the core function without any redundant information. It earns full marks for efficiency.
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's simplicity, rich annotations, and presence of an output schema, the description is minimally adequate. However, it does not differentiate this lookup from many similar sibling tools, and it lacks details about when to use it or what 'free-text' entails, leaving some gaps for an agent relying solely on the description.
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 only 50% (the 'rows' parameter has a description, but 'query' does not). The description's mention of 'free-text query' provides some semantic context for the otherwise undocumented query parameter, but it does not fully compensate for the coverage gap or add details about acceptable formats or behavior.
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 ('lookup') and resource ('author'), clearly identifying the tool's function as author retrieval. It is more specific than generic sibling tools like 'search' or 'get', but does not elaborate on what constitutes an 'author' or the exact scope, so it stops short of a 5.
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 on when to use this tool versus alternatives such as 'search', 'resolve_entity', or 'entity_profile'. The description lacks any indications of preferred scenarios, exclusions, or relationships to sibling tools.
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.
Several tools occupy nearly the same role: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are deliberately near-duplicates, while deep_research, validate_claim, bet_research, and the polymarket_* family all route factual questions to overlapping data pipelines. Generic single-word tools like get, search, structure, and author add further ambiguity, making it hard for an agent to confidently pick the right tool.
Names are consistently lowercase snake_case, but they mix verb_noun tools (list_subscriptions, resolve_entity, validate_claim) with bare nouns (author, get, search, structure) and domain-prefixed families (ask_pipeworx, polymarket_*, pipeworx_*). The conventions are readable but not predictable enough to infer behavior from the name alone.
35 tools is heavy for a single server, especially when many are meta-routers or near-variants of each other. The broad data-research scope justifies some breadth, but the surface feels padded with overlapping research and prediction-market tools rather than a tight, well-scoped set.
For its apparent purpose — authoritative data lookup, verification, research, entity profiling, prediction-market analysis, and monitoring — the surface is largely complete: retrieval, grounded answers, deep research, comparison, change tracking, subscriptions, and memory are all covered. Minor gaps exist, such as no direct tool for managing alert delivery or for some of the vague HAL-style operations, but agents can work around these via the router tools.