suggestTitle/artist suggestions for a free-form query (results have track + artist info).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | 1-50 (default 10) | |
| query | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | Array of track suggestions with artist info | |
| total | Yes | Total number of suggestions available |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "query": "bohemian rhapsody"
+ },
+ {
+ "limit": 5,
+ "query": "love songs"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "data": {
+ "description": "Array of track suggestions with artist info",
+ "items": {
+ "properties": {
+ "artist": {
+ "description": "Artist information",
+ "type": "object"
+ },
+ "title": {
+ "description": "Song title",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "total": {
+ "description": "Total number of suggestions available",
+ "type": "number"
+ }
+ },
+ "required": [
+ "total",
+ "data"
+ ],
+ "type": "object"
+}Input schema / examplesRemoved value: -[
- {
- "query": "bohemian rhapsody"
- },
- {
- "limit": 5,
- "query": "love songs"
- }
-]Output schema / (root)Previous value: -{
- "properties": {
- "data": {
- "description": "Array of track suggestions with artist info",
- "items": {
- "properties": {
- "artist": {
- "description": "Artist information",
- "type": "object"
- },
- "title": {
- "description": "Song title",
- "type": "string"
- }
- },
- "type": "object"
- },
- "type": "array"
- },
- "total": {
- "description": "Total number of suggestions available",
- "type": "number"
- }
- },
- "required": [
- "total",
- "data"
- ],
- "type": "object"
-}New value: +nullInput schema / examplesAdded value: +[
+ {
+ "query": "bohemian rhapsody"
+ },
+ {
+ "limit": 5,
+ "query": "love songs"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "data": {
+ "description": "Array of track suggestions with artist info",
+ "items": {
+ "properties": {
+ "artist": {
+ "description": "Artist information",
+ "type": "object"
+ },
+ "title": {
+ "description": "Song title",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "total": {
+ "description": "Total number of suggestions available",
+ "type": "number"
+ }
+ },
+ "required": [
+ "total",
+ "data"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, covering safety and idempotency. The description adds minimal behavioral context (returning track+artist info) beyond the annotations. No contradictions.
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 12-word sentence, highly concise and front-loaded. It could be slightly more structured (e.g., bullet points) but is efficient.
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?
With an output schema present, return values are documented. The description covers input (free-form query) and output (track+artist info) adequately for a simple suggestion tool. Could mention scope or edge cases, but it's generally sufficient.
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 50% (only 'limit' has description). The description explains 'query' as 'free-form query', adding some context, but does not elaborate on 'limit' beyond its schema description. Baseline 3 is appropriate given partial coverage.
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 ('suggest'), the resource ('Title/artist suggestions'), and the input context ('free-form query'), while also noting the output includes track and artist info. This effectively distinguishes it from sibling tools like 'lyrics' or 'search_within'.
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 usage for open-ended music queries but does not explicitly state when to use this tool versus alternatives (e.g., 'lyrics' for lyrics, 'search_within' for other searches). No exclusions or when-not-to-use guidance is provided.
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 have overlapping purposes. ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded all route to the same 5,564 tools, differing only in grounding behavior. suggest and lyrics both look up music but in different ways; suggest is broader while lyrics is exact. The core tools are distinct, but the multiple pipeworx variants and music tools create ambiguity.
Naming is highly inconsistent. Most tools use snake_case (ask_pipeworx, entity_profile, compare_entities), but several use verb phrases (generate_llms_txt, scan_competitor_ai_presence) and some use short nouns (lyrics, suggest). There's no consistent verb_noun pattern; 'ask_pipeworx' variants mix imperative with domain words, and 'recall'/'remember' are verbs without objects.
With 33 tools, the server covers a wide domain (company research, prediction markets, news, weather, lyrics, memory, subscriptions, etc.). While this is many tools, each has a specific purpose and the variety matches the stated 'universal router' / 'thousands of data sources' value prop. It could be trimmed slightly, but the count is justified by the breadth.
The tool surface is remarkably complete for its stated purpose: unstructured lookup (ask_pipeworx), grounded verification (ask_pipeworx_grounded), deep multi-source research (deep_research), entity profiles, comparisons, change feeds, arbitrage scanning, memory, subscriptions, and even feedback/governance tools. It covers all common patterns in data retrieval and has distinct tools for edge cases, making it hard to find obvious gaps.