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list_collections

Read-onlyIdempotent

List all public collections as name/slug pairs. Use the collection slug as the collection ID string when browsing works. Optional browse filters also return live facets for collections, dynasties and types; the static list stays complete.

Input Schema

NameRequiredDescriptionDefault
tagNoWork kind slug from list_types: shi (诗), ci (词), qu (曲), wen (文).
categoryNoDynasty name from list_dynasties, for example 唐. Not a group name.
collectionNoCollection ID string from list_collections, for example "1".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare read-only, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely new behavior: it is public-scoped only, and passing browse filters returns live facets while the static list 'stays complete' — a non-obvious side effect an agent would otherwise not predict.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the core action and return shape, with no filler. The facet sentence is densely compressed ('Optional browse filters also return live facets') and reads slightly ambiguously about what the filters affect.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, yet the description discloses the return shape (name/slug pairs) and the facet behavior, which is what an agent needs to invoke and interpret it. For a zero-required-parameter listing tool with full annotation coverage, only the filter semantics remain slightly under-explained.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3; the description earns above that by explaining what the optional filters actually do — they trigger live facet computation for collections, dynasties and types rather than narrowing the returned list. It does not restate per-parameter formats, which the schema already handles.

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?

States a specific verb and resource ('List all public collections') plus the return shape ('name/slug pairs'), which an agent can distinguish from list_dynasties, list_types or list_groups by resource name alone. It does not explicitly contrast itself with the nearest sibling (list_groups), so it stops short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives a concrete downstream usage rule: take the collection slug and use it as the collection ID string when browsing works. That tells the agent when to reach for this tool, but it offers no exclusions or explicit alternative (e.g. when to prefer list_groups).

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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