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scholarfetch_saved_list

List all papers currently saved in a named in-memory reading list. Use this to inspect the working set before exporting or removing items.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
collectionNodefault

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It notes the list is 'in-memory' and 'currently saved', indicating an ephemeral, read-only state, but it does not explicitly state that the tool causes no side effects or that it does not modify the list.

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

Conciseness5/5

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

The description is two sentences, front-loaded with the core action, and contains no redundant information. Every word adds value.

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

Completeness3/5

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

The tool is simple with one optional parameter and an output schema, so return structure is covered elsewhere. However, the description fails to compensate for the missing parameter semantics and does not fully articulate the read-only nature, leaving gaps for an agent to infer.

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

Parameters2/5

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

The schema has one parameter 'collection' with 0% schema description coverage, and the description does not explicitly explain this parameter. It only mentions a 'named' list, which hints at the connection but does not clarify that 'collection' is the list name, its valid values, or its default behavior.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool lists papers saved in a named reading list with the verb 'List' and resource 'papers currently saved in a named in-memory reading list'. It distinguishes from siblings like saved_add, saved_remove, and saved_export by focusing on inspection/listing.

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?

The description gives explicit context for use: 'Use this to inspect the working set before exporting or removing items.' This tells the agent when to invoke it, though it lacks direct exclusions or mentions of alternative tools.

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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TDQS

A4.2/5.0
Disambiguation5/5

Each tool targets a distinct operation: searching, DOI lookup, author disambiguation, paper listing, abstract/full-text retrieval, reference expansion, and saved-list management. No two tools overlap in purpose, and the descriptions clearly differentiate entry points (DOI vs. author vs. keyword) and output types.

Naming Consistency4/5

All tools share the 'scholarfetch_' prefix and use lowercase snake_case, but the second part mixes nouns (abstract, article_text, references) with verb phrases (saved_add, doi_lookup, search). This is a minor deviation from a strict verb_noun pattern, but the overall pattern remains predictable and readable.

Tool Count5/5

With 12 tools, the server is well-scoped for academic literature retrieval and management. Each tool has a clear role, and the count is within the ideal range, providing a complete workflow without unnecessary bloat.

Completeness5/5

The tool surface covers the full research process: discovery (search, DOI lookup), author exploration (candidates, papers), reading (abstract, full text), citation traversal (references), and library management (saved add/list/remove/export). No obvious gaps exist for the stated purpose.