AgentAI
Server Details
AI/ML research intelligence — HuggingFace trending papers with upvotes, arXiv AI/ML subcategory search (cs.LG, cs.AI, cs.CL, cs.CV), and DBLP CS bibliography. Built for AI agents researching the latest in machine learning.
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- Healthy
- Last Tested
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- Streamable HTTP
- URL
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Tool Definition Quality
Average 3.4/5 across 3 of 3 tools scored.
Each tool targets a different source (HuggingFace, arXiv, DBLP) with slightly different retrieval modes (trending, keyword search, publication search). Some overlap exists since all return papers, but descriptions clearly distinguish the underlying database and behavior.
Two tools use 'search_' prefix and one uses 'get_', but all follow a verb_source pattern. The inconsistency between 'get' and 'search' is minor; overall naming is clear and predictable.
Three tools is a small but focused set for a paper retrieval server. It's slightly thin for a broad AI/ML domain, but the selected sources (HuggingFace, arXiv, DBLP) cover major repositories, making the count reasonable.
The tools cover trending and keyword search across three sources, but missing features like fetching full paper details, saving or managing papers, or cross-source aggregation. Core search functionality is present, but agents may need additional retrieval capabilities.
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.
| 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
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully cover behavior. It only states return type (trending/search results) but omits details like authentication, rate limits, error handling, or response format. Basic but insufficient.
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?
Two sentences with no wasted words. Front-loaded with the core action (get papers) and mode of operation. Perfectly concise for the information conveyed.
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 no output schema and no annotations, the description covers the main functionality adequately. It explains both modes (trending by date, search by keyword). Could mention limit default/max, but schema already provides that. Slightly incomplete on return format, but acceptable for a simple tool.
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 100%, so baseline is 3. The description adds minor context (e.g., 'search results by keyword' maps to q, 'given date' maps to date) but does not significantly enhance understanding beyond the schema.
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 tool retrieves trending or searched AI/ML research papers from HuggingFace Papers, with specific mentions of date or keyword search. It distinguishes itself from sibling tools (search_arxiv_ai, search_dblp) by source and mode.
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 fetching HuggingFace papers but provides no explicit guidance on when to use this tool over siblings or when not to use it. No exclusions or alternatives are 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.
| 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
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, leaving the description as the sole source of behavioral info. The only disclosed trait is that results are recent and sorted by date. Missing details like authentication needs, rate limits, error handling, or pagination behavior.
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, consisting of a single sentence that is front-loaded with the key action. Every word serves a purpose, with no filler or redundancy.
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?
The description states the return value ('recent submissions sorted by date'), which is helpful given no output schema. However, it does not describe the structure or format of the results, which could be ambiguous for an agent. Adequate but not fully complete.
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 input schema has 100% description coverage, so the baseline is 3. The description does not add meaning beyond what the schema already says (e.g., 'keyword' and 'category' are already described). No extra parameter semantics are provided.
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 tool's purpose: searching arXiv for AI/ML papers by keyword and category. It uses a specific verb ('search') and resource ('arXiv for AI/ML papers'), but does not explicitly differentiate from sibling tools like 'get_ai_papers' or 'search_dblp'.
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 when to use the tool (when looking for recent AI/ML papers on arXiv by keyword/category), but it does not provide explicit guidance on when to use alternatives or exclude cases. No when-not-to-use information is given.
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.
| 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
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It only states 'Free, no key required' but does not disclose rate limits, pagination, sorting behavior, or return format.
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 sentence, efficient and front-loaded, but could include more behavioral context without becoming verbose.
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?
Lacks output schema and does not describe return format. Differentiates from siblings only by database source, which is minimal context.
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 100% with parameter descriptions for q, limit, and author. The description does not add significant new meaning beyond what the schema provides.
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 'Search', the resource 'DBLP computer science bibliography', and the objects 'publications or authors'. It is distinct from sibling tools like search_arxiv_ai and get_ai_papers.
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 mentions 'Free, no key required' which gives a usage condition but does not explicitly state when to use this tool versus alternatives or provide exclusion criteria.
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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