A
licenseB
qualityF
maintenanceSearch and retrieve academic papers from arXiv and DBLP databases, with AI-powered prompts to generate comprehensive research summaries, discover related topics, and identify leading authors in any field.
2
2
MIT
AI/ML Research Papers
Server Details
AI/ML research papers from arXiv, DBLP, and HuggingFace
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
A3.6/5.0
Tool DescriptionsB
Average 3.2/5 across 3 of 3 tools scored.
Server CoherenceA
Disambiguation5/5
Each tool targets a distinct data source: HuggingFace Papers, arXiv, and DBLP. Their purposes are clearly differentiated by source and search type, with no overlap.
Naming Consistency4/5
All names use lowercase and underscores, but one uses 'get' while two use 'search', creating a slight inconsistency. Otherwise, the pattern is clear.
Tool Count5/5
Three tools is appropriate for a research papers server, covering three major sources without being too few or too many.
Completeness4/5
The server covers searching across three key AI/ML databases, which is adequate for discovery. Minor gaps exist, such as the lack of a tool to fetch paper details by ID.
Available Tools
3 toolsget_ai_papersAInspect
Get trending or searched AI/ML research papers from HuggingFace Papers. Returns trending papers for a given date or search results by keyword.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | Search query (for type=search) | |
| date | No | Date for trending papers (YYYY-MM-DD, default: yesterday) | |
| type | No | trending or search (default: trending) | trending |
| limit | No | Number of results (max 25) |
Tool Definition Quality
A3.5/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only restates the parameter-driven behavior already covered by the schema (returns trending papers for a given date or search results by keyword) without disclosing additional behavioral traits like pagination, rate limits, or expected response format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that begins with the verb and purpose. It is concise with no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters, no output schema, and no annotations, the description is adequate but leaves gaps. It does not explain the mutual exclusivity of 'q' and 'date' relative to 'type', nor does it describe the response structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no new meaning beyond the schema; it mentions 'trending' and 'search' but does not clarify parameter relationships or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'trending or searched AI/ML research papers from HuggingFace Papers'. It distinguishes the tool from siblings (search_arxiv_ai, search_dblp) by specifying the source as HuggingFace Papers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage scenarios (trending by date or search by keyword) but does not explicitly state when to use this tool versus the sibling tools. There is no when-not guidance or alternatives mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_arxiv_aiBInspect
Search arXiv for AI/ML papers by keyword and category. Returns recent submissions sorted by date.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | Keyword search query | large language model |
| limit | No | Number of results (max 20) | |
| category | No | arXiv category: cs.AI, cs.LG, cs.CL, cs.CV, cs.RO, stat.ML (default: cs.LG) | cs.LG |
Tool Definition Quality
B3.1/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description must disclose behavior. It only says 'returns recent submissions sorted by date,' omitting details like rate limits, read-only nature, or result structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the verb and resource. No wasted words; every part earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 parameters and no output schema, the description covers the basic action but lacks details on return fields or pagination. It is adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all 3 parameters (q, limit, category). The tool description adds no extra meaning beyond what the schema already provides, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool searches arXiv for AI/ML papers using keyword and category, which is specific and clear. However, it does not differentiate from sibling tools like get_ai_papers or search_dblp, lacking contrast.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description implies general search use but provides no preconditions, exclusions, or context for choosing it over siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_dblpBInspect
Search DBLP computer science bibliography for publications or authors. Free, no key required.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | Publication search query | transformer attention |
| limit | No | Number of results (max 25) | |
| author | No | Search by author name instead of publication title |
Tool Definition Quality
B3.1/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It mentions 'Free, no key required' which is a positive behavioral trait, but it does not disclose whether the tool is read-only, rate limits, or any other behavioral details. For a search tool, such information is important.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: a single sentence that front-loads the action. Every word adds value, with no superfluous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has three parameters and no output schema, the description is somewhat minimal. It covers the basic purpose but lacks details on return format, pagination (though limit is mentioned), and when to use this tool over siblings. It is adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% as all three parameters have descriptions. The tool description adds context about searching for publications or authors, which aligns with the author parameter, but does not provide additional parameter-specific meaning beyond what the schema already offers.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches DBLP for publications or authors, using a specific verb and resource. It also notes it's free and requires no key, which adds clarity. However, it does not explicitly differentiate from sibling tools like get_ai_papers or search_arxiv_ai.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. The description only states what it does, without any when-to-use or when-not-to-use information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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