ipnex
Server Details
Cited, confidence-stamped patent intelligence over US university tech-transfer out-licensing.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.2/5 across 2 of 2 tools scored.
The two tools have clearly distinct purposes: 'get_technology' is for fetching a specific technology by its TTO docket, while 'search_licensable_ip' is for searching across licensable US university patent technologies. There is no overlap in their core functionality.
Both tools follow a consistent verb_noun pattern in snake_case: 'get_technology' and 'search_licensable_ip'. The verbs are appropriate for the actions, and the naming is predictable and clear.
With only two tools, the server is on the thin side for its domain. While each tool is detailed and serves a core purpose, a typical well-scoped server has 3-15 tools. The small count may limit the agent's ability to perform common tasks like listing all technologies or filtering results without search.
The two tools cover the essential operations for the domain: retrieving a specific technology and searching across technologies with rich filters and metadata. Minor gaps exist, such as the lack of a tool to list all institutions or browse by category, but the search tool's facets partially compensate.
Available Tools
2 toolsget_technologyAInspect
Fetch the published view of one technology by its TTO docket. Cited + confidence-stamped; point-in-time via 'as_of'. Patent data: Google Patents (CC BY 4.0) + USPTO (public domain). Summaries are IPNEX-authored. TTO listing content is linked, not reproduced.
| Name | Required | Description | Default |
|---|---|---|---|
| as_of | No | ISO-8601 timestamp for the point-in-time published view. | |
| docket | Yes | The TTO docket id, e.g. 'P160232US05', 'S17-467'. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses data sources (Google Patents, USPTO), licensing (CC BY 4.0, public domain), authorship of summaries (IPNEX-authored), and that TTO listing content is linked not reproduced. It also notes that results are cited and confidence-stamped, with point-in-time via 'as_of'. This provides good behavioral context, though it could mention that it's a read-only operation.
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 three sentences, front-loading the purpose in the first sentence. Each sentence adds unique information: core function, features, and data provenance. No redundancy or unnecessary words.
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 (2 parameters, no output schema, no annotations), the description covers key aspects: purpose, data sources, licensing, point-in-time, and the nature of TTO content. It doesn't detail return format, but the mention of citations, confidence stamps, and linked content provides enough context for an agent to understand what to expect.
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%, so baseline is 3. The description adds value by explaining the 'as_of' parameter's purpose ('point-in-time') and that the docket parameter is used for fetching a specific technology. This goes beyond the schema descriptions, adding meaningful context.
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 'Fetch' and the resource 'published view of one technology by its TTO docket', distinguishing it from the sibling tool 'search_licensable_ip' which is for searching. It also mentions the point-in-time feature via 'as_of', making the purpose highly specific.
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 context: use this tool when you have a specific TTO docket to fetch a single technology's published view. It doesn't explicitly state when not to use it or mention alternatives, but the sibling tool name makes the distinction clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_licensable_ipAInspect
Search published, licensable US university patent technologies. Answers 'what currently-Active US university IP is licensable from X?'. Every result is cited (Google Patents / USPTO), confidence-stamped, and carries an 'ownership' signal flagging whether the patent's current assignee of record is the marketing institution or a third party, a 'status' interpretation flagging public-domain (term-expired) vs revivable fee-lapsed vs in-force patents, and an 'expiry' reading of how many years of exclusive term remain (expired / expiring_soon / active_term). The response also carries 'facets' -- corpus-level breakdowns over all matches by ownership, institution, status, status_detail, and expiry (the whole-query split, without paging). Patent data: Google Patents (CC BY 4.0) + USPTO (public domain). Summaries are IPNEX-authored. TTO listing content is linked, not reproduced.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results to return (confidence-sorted). | |
| status | No | Legal-status substring, e.g. 'Active', 'Expired'. | |
| keyword | No | Substring matched against the title and our summary. | |
| institution | No | Marketing institution substring, e.g. 'Wisconsin', 'Stanford'. | |
| min_confidence | No | Drop results below this join confidence (0-1). | |
| licensable_from_institution | No | When true, exclude hits whose patent's current assignee of record is positively not the marketing institution (assigned-away or third-party owned); honest-unknowns are kept. Default false. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description provides substantial behavioral details: each result is cited, confidence-stamped, and carries ownership, status, and expiry signals. It also describes 'facets' and data sources. Minor gaps remain, such as pagination or rate limits, but overall transparency is high.
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 relatively long but well-structured. It front-loads the core purpose and then details output features. While every sentence adds value, it could be slightly more concise without losing information.
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 6 parameters, no output schema, and no annotations, the description is remarkably complete. It explains response structure, data sources, authorship, and facets. It adequately prepares an agent to use the tool correctly.
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%, so the schema already describes all 6 parameters. The description adds context for the overall behavior (e.g., confidence-sorted results) but does not add significant meaning to individual parameters beyond their schema descriptions.
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 precisely states the tool's purpose: searching published, licensable US university patent technologies. It answers a specific question and distinguishes from the sibling tool 'get_technology', which likely retrieves a single technology.
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 searching licensable IP but does not explicitly state when to use this tool versus alternatives or exclude scenarios. No guidance on when not to use.
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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