scholarlyFetch a single Lens.org scholarly work by its lens_id (requires Bearer token); returns full metadata including abstract, authors, citations, and open-access links.
| Name | Required | Description | Default |
|---|---|---|---|
| lens_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "lens_id": "178527186"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "description": "Single scholarly work record from Lens.org API",
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint false. Description adds value by noting authentication requirement and listing return fields (abstract, authors, citations, open-access links). No contradictions 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?
Single sentence, no redundant words. Front-loaded with main action. Every word 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?
With output schema present, description adequately covers primary return information. Lacks details on error behavior for invalid lens_id. But for a simple one-parameter fetch tool, it's largely 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 coverage is 0%, so description must compensate. It provides context that the parameter is a Lens.org identifier but does not specify format, constraints, or validation rules beyond the example. More detail needed for the single parameter.
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?
Description uses specific verb 'Fetch' and identifies the resource as 'a single Lens.org scholarly work by its lens_id'. It clearly distinguishes from the sibling 'scholarly_search' by specifying single work retrieval.
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?
Description mentions requirement of Bearer token, which is a usage prerequisite. However, it does not explicitly state when to use this tool versus alternatives like 'scholarly_search', nor does it provide exclusion criteria.
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 clusters have unclear boundaries: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are three variants of the same router (beta is currently identical), while bet_research, polymarket_edges, and polymarket_arbitrage all target prediction-market opportunities. ai_visibility_check is effectively a single-entity version of scan_competitor_ai_presence, and discover_tools overlaps heavily with suggest_questions.
Tool names are uniformly snake_case and descriptive, but the pattern is mixed: verb-first names (ask_pipeworx, compare_entities, search_within) coexist with noun-first names (patent, scholarly, entity_profile), and the Lens.org pairing of patent/patents_search vs scholarly/scholarly_search is structurally inconsistent. Subgroups like pipeworx_* and polymarket_* are internally consistent, keeping the overall set readable.
At 35 tools, this exceeds the 16-25 'heavy' band and bundles at least four distinct domains: Lens.org bibliometrics, Pipeworx data routing, Polymarket trading analysis, and memory/subscription utilities. While many tools serve legitimate purposes, the set feels sprawling and several variants (e.g., the three ask_pipeworx flavors) inflate the count without adding equivalent value.
The Pipeworx/Polymarket ecosystem is thoroughly covered with routing, grounded answers, deep research, entity resolution, validation, comparison, monitoring, and memory all present. The Lens.org portion is thin (search + fetch for patents and scholarly works) but covers the core read path; minor gaps exist such as no batch/export operations and no patent-number lookup.