Read the full content of one fascicle (卷) of a text, with its urn.
Use the `text_id`/`juan_num` from a search_corpus hit. Returns the actual
canonical text — quote from this, not from memory.
| Name | Required | Description | Default |
|---|---|---|---|
| text_id | Yes | ||
| juan_num | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden for behavioral disclosure. It states it returns the actual canonical text, implying authoritative content, and 'full content' suggests no truncation, but it does not mention authentication, rate limits, errors, or output size, leaving notable 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 only two sentences, front-loading the purpose and immediately providing usage instructions. It is free of redundant words and does not repeat schema 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?
For a simple read operation with two parameters and no output schema, the description covers what it does, how to use it, and what it returns. It omits edge-case behavior, but given the tool's simplicity, this is acceptable and the description feels 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 schema has no parameter descriptions, so the description compensates by explaining that text_id and juan_num come from search_corpus hits and that juan_num corresponds to a fascicle. This is essential context for correctly supplying values, though it does not give formal definitions.
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 reads the full content of one fascicle of a text, with the verb 'read' and resource 'fascicle' specifying the exact action. It also distinguishes itself from siblings like search_corpus by noting it returns actual canonical text rather than hits.
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?
It explicitly instructs to use text_id and juan_num from a search_corpus hit, establishing a clear workflow and when to use the tool. It also advises to quote from the returned text rather than memory, providing practical usage guidance, though it does not compare with other sibling tools.
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.
Each tool targets a distinct resource or operation: commentaries for historical glosses, get_parallels for cross-tradition alignments, lookup_dictionary for terms, lookup_entity for entities, read_passage for full text, resolve_urn for citation resolution, search_corpus for semantic search, and verify_quote for verbatim verification. There is no overlap in purpose, and the boundaries are clear even between similar-looking lookups.
Most tool names follow a consistent verb_noun snake_case pattern (get_parallels, lookup_dictionary, read_passage, resolve_urn, search_corpus, verify_quote). The lone exception is 'commentaries,' which is a noun rather than a verb_noun construction, but this is a minor deviation in an otherwise uniform set.
With 8 tools, this server is well-scoped for a specialized Buddhist canon research domain. Each tool earns its place, covering search, retrieval, verification, lookup, and cross-reference without redundancy or bloat.
The toolset covers the complete research workflow: finding passages (search_corpus), reading them (read_passage), verifying quotes (verify_quote), resolving citations (resolve_urn), understanding terms (lookup_dictionary) and entities (lookup_entity), and exploring cross-tradition parallels (get_parallels) and commentaries (commentaries). No significant gaps exist for the stated purpose.