JAIL Search
Server Details
Search a billion+ documents — papers, books, code, legal cases, forums, Wikipedia, and more.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- mefengl/jail-mcp
- GitHub Stars
- 0
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Tool Definition Quality
Average 3.8/5 across 2 of 2 tools scored.
The two tools have clearly distinct and complementary purposes: 'search' retrieves a ranked list of documents with basic metadata, while 'detail' provides full metadata for a specific document ID from search results. There is no overlap or ambiguity between them, as they represent different stages in a search workflow.
Both tool names follow a consistent, simple verb-based pattern ('search' and 'detail') that is intuitive and aligned with their functions. The naming is straightforward and predictable, with no deviations or mixed conventions.
With only two tools, the server feels minimal but functional for its search-focused purpose. It covers the core operations of searching and retrieving details, but the count is borderline thin, potentially limiting advanced interactions like filtering or saving results. However, it is adequate for basic search tasks.
For a search server, the tools provide essential coverage: 'search' for finding documents and 'detail' for in-depth metadata. Minor gaps exist, such as no explicit tools for filtering, sorting, or managing search history, but the core workflow is complete and agents can work effectively with the provided tools.
Available Tools
2 toolsdetailBInspect
Get full metadata for a document. Use IDs from search results.
| Name | Required | Description | Default |
|---|---|---|---|
| doc_id | Yes | Document ID from search results (e.g. "md5:abc123...", "hn:19415066", "doi:10.1038/...") |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While it indicates this is a read operation ('Get'), it doesn't describe what 'full metadata' includes, whether there are rate limits, authentication requirements, or error conditions. For a tool with no annotation coverage, this leaves significant gaps.
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 with two short sentences that are front-loaded and waste no words. Every sentence adds value: the first states the purpose, and the second provides usage context.
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 tool's simplicity (1 parameter, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose and usage but lacks details on behavioral aspects like what metadata is returned or any operational constraints, which are important for a tool with no annotations.
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 schema description coverage is 100%, with the parameter 'doc_id' fully documented in the schema. The description adds minimal value by reinforcing that IDs come from search results, but doesn't provide additional syntax or format details beyond what the schema already specifies.
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 with a specific verb ('Get') and resource ('full metadata for a document'), making it easy to understand what it does. However, it doesn't explicitly distinguish this from its sibling 'search' tool beyond mentioning IDs come from search results.
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 implied usage guidance by stating 'Use IDs from search results,' which suggests this tool should be used after obtaining document IDs from the 'search' tool. However, it doesn't explicitly state when to use this versus alternatives or any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
searchAInspect
Search documents. Returns ranked results with title, author, year, description, url, id, score — not full content. Use URLs from results with fetch/browsing to read actual documents.
Use when: user asks to research, find papers/books/articles, look up facts, find discussions, legal cases, or any "search for..." request.
Strategy: use 2-4 keywords per query (English preferred). Pick the right type first. Try synonyms if few results. Search across multiple types to cross-reference. Use detail() for full metadata on promising results.
| Name | Required | Description | Default |
|---|---|---|---|
| type | Yes | Content type (required). academic: OpenAlex/arXiv/Semantic Scholar/DBLP | wiki: Wikipedia 18 languages | books: books/digital libraries | legal: Case Law/CourtListener/EUR-Lex | forums: HN/StackExchange/Lobsters/LessWrong/60+ | economics: World Bank/IMF/FRED | packages: npm/PyPI/Crates.io | knowledge: Wikidata | news: news articles | music: Discogs/MusicBrainz | video: IMDb/YouTube | health: clinical trials | geo: world places | fandom: fan wikis | tech: Dev.to | audio: podcasts | social: Reddit/Mastodon/Lemmy | crypto: DeFi/tokens | predictions: prediction markets. | |
| limit | No | Results to return (1-50). Trial max 10, Pro max 50. | |
| query | Yes | Search query — use 2-4 keywords for best results. English preferred unless searching non-English content. Try different keywords and synonyms if first attempt returns few results. | |
| cursor | No | Opaque pagination token. Use next_cursor from previous response. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: it returns ranked results with specific fields (not full content), requires using URLs with fetch/browsing to read actual documents, and includes strategy guidance (2-4 keywords, English preferred, try synonyms, search across types). However, it doesn't mention rate limits, authentication needs, or error conditions.
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 well-structured with clear sections: purpose, usage guidelines, and strategy. It's appropriately sized with no wasted sentences—each contributes value. However, the strategy section could be slightly more concise as it overlaps somewhat with parameter guidance already in the schema.
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 tool's complexity (search across multiple content types) and lack of annotations/output schema, the description does a good job of providing context. It explains what the tool returns, when to use it, and basic strategy. However, it could benefit from more detail on result format limitations or error handling to be 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?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal parameter semantics beyond what's in the schema—it reinforces the '2-4 keywords' guidance for the query parameter and mentions 'Pick the right type first' for the type parameter. This provides some additional context but doesn't significantly enhance the schema's documentation.
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: 'Search documents. Returns ranked results with title, author, year, description, url, id, score — not full content.' It specifies the verb (search), resource (documents), and output format, distinguishing it from the sibling 'detail' tool which provides full metadata on specific results.
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 explicit usage guidelines: 'Use when: user asks to research, find papers/books/articles, look up facts, find discussions, legal cases, or any "search for..." request.' It also mentions when to use the sibling tool: 'Use detail() for full metadata on promising results.' This gives clear context for when to use this tool versus alternatives.
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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