objectQuery by object name (resolved via SIMBAD/NED).
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| catalog | No | Optional catalogue id; default queries all. |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "name": "Sirius"
+ },
+ {
+ "catalog": "I/345/gaia2",
+ "name": "M31"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "description": "Object name query results (resolved via SIMBAD/NED)",
+ "oneOf": [
+ {
+ "additionalProperties": true,
+ "properties": {},
+ "type": "object"
+ },
+ {
+ "properties": {
+ "body": {
+ "description": "Raw text response (first 4000 chars)",
+ "type": "string"
+ },
+ "format": {
+ "description": "Format indicator when JSON parsing fails",
+ "enum": [
+ "raw"
+ ],
+ "type": "string"
+ }
+ },
+ "required": [
+ "format",
+ "body"
+ ],
+ "type": "object"
+ }
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds that resolution is via SIMBAD/NED, which is useful context but does not disclose further behavioral traits.
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 concise sentence, front-loaded with the key purpose. No wasted words, though it could benefit from a bit more detail.
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 simple 2-parameter tool and presence of an output schema, the description is minimally adequate but omits details like pagination or behavior on no results.
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 description adds little meaning beyond the schema: it mentions 'object name' but does not explain input formats or valid catalog IDs. With 50% schema coverage, the description should compensate but fails to do so.
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 verb 'Query' and resource 'object name', and mentions the resolution via SIMBAD/NED. However, it does not differentiate from sibling tools like 'resolve_entity' or 'catalogs'.
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 provides no guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions.
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.
Multiple tool groups have unclear boundaries: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, suggest_questions, and validate_claim all route questions or discovery; ai_visibility_check and scan_competitor_ai_presence duplicate the same probe; polymarket_edges, polymarket_arbitrage, and bet_research all scan prediction markets. The descriptions are detailed, but the set itself gives agents too many overlapping entry points to choose from.
Tool names are almost universally snake_case and mostly follow a verb_noun pattern (compare_entities, resolve_entity, list_subscriptions, generate_llms_txt). There are minor deviations like bare nouns 'catalogs' and 'object', and 'entity_profile' is noun_noun, but the overall pattern is recognizable and consistent enough.
35 tools is beyond the 25+ 'too many' threshold and the server bundles five or six distinct domains (astronomy, financial data, prediction markets, memory, subscriptions, and web utilities). While each subdomain has its own scope, the total count makes the tool surface feel like a kitchen sink rather than a coherent, well-scoped server.
Each subdomain has decent coverage: memory has remember/recall/forget, subscriptions have subscribe/list/unsubscribe/recent_alerts, and the data cluster has ask/grounded/deep/validate/profile/compare variants. However, the overall domain is fragmented, there is no subscription update mechanism, and the advertised pipeworx:// citation URIs rely on MCP resources rather than a tool—leaving some workflows with dead ends.