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Scholar Feed

by io.github.YGao2005

List Library

list_library
Read-only

List the authenticated user's saved papers (their library), newest first. Read-only. Use this to review a reading list or to see what's already saved before saving more. Requires SF_API_KEY. SHAPE: agent callers get a lean record — llm_summary (~300 chars) INSTEAD of the abstract, with empty fields omitted rather than sent as null. Each paper also carries the state that makes this a knowledge base rather than a bookmark list: note_text (the user's own recorded verdict, when one exists), is_read, and collections (the axes it is filed under, e.g. 'AgentOPA/G4'). READ note_text FIRST. A paper carrying one was already judged in an earlier session — use that verdict instead of re-reading the paper and re-deriving it. If it is missing, consider recording one with annotate_paper so the next session inherits your conclusion. Pass verbose=true (or fields=...) only when you genuinely need the abstract or the full 28-field shape; the default is ~4x smaller and is the right choice for surveying what you already have.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number for paging through a large library.
limitNoHow many saved papers to return (max 100).
fieldsNoComma-separated fields to return, e.g. 'arxiv_id,title,abstract'. Overrides verbose. Library state (note_text/is_read/is_saved/collections) is always included regardless.
verboseNoReturn the full paper shape (including the abstract) instead of the lean default. Costs roughly 4x the tokens — prefer llm_summary unless you specifically need the abstract's wording.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoSearch mode actually applied.
noteNo
pageNo
sortNoSearch sort order actually applied.
limitNo
topicNo
totalNoTotal results available for the query. null when the count was skipped (query-less browse, or the count query timed out).
papersNoMatched / returned papers.
directionNoCitation direction (get_citations: citing | cited_by).
not_foundNoRequested IDs that had no match.
next_cursorNoKeyset cursor for the next page, or null when exhausted.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Even though annotations already declare readOnlyHint=true and destructiveHint=false, the description goes far beyond them. It discloses the lean response shape (llm_summary instead of abstract, empty fields omitted), the knowledge-base fields (note_text, is_read, collections), and behavioral instructions like 'READ note_text FIRST' to reuse prior verdicts. Also it exposes token cost implications of verbose mode. This is rich, non-redundant transparency.

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 longer than average, but every sentence earns its place. It is front-loaded with purpose and usage, then structured into SHAPE and parameter guidance. The formatting with capitalization and line breaks makes it scannable for an agent, and there is no filler or repetition of schema defaults.

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

Completeness5/5

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

For a read-only listing tool, this description is complete: it states the auth requirement (SF_API_KEY), explains the default versus verbose response shape, describes the state fields that matter for downstream decisions, and provides actionable guidance for the agent. The output schema also exists, so return-value documentation is structurally covered. Nothing an agent needs to call this correctly is missing.

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 schema already documents all four parameters. The description adds meaningful context beyond the schema: it explains that verbose is ~4x more token-expensive, that the default lean shape is the right choice for surveying, and that fields overrides verbose while state fields are always included. It does not add new semantics for page/limit, but the existing schema descriptions are sufficient, and the added guidance improves parameter selection.

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 opens with a specific verb and resource: 'List the authenticated user's saved papers (their library), newest first.' This unambiguously distinguishes it from sibling tools like search_papers (search), get_paper (single retrieval), and save_paper (writing). It also states the ordering, making the tool's scope immediately clear.

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 explicitly states when to use the tool: 'Use this to review a reading list or to see what's already saved before saving more.' It also provides guidance on when to use verbose mode ('only when you genuinely need the abstract') and suggests a follow-up action with annotate_paper. However, it does not explicitly exclude alternatives by name (e.g., 'use search_papers for discovery'), so it stops short of a full when-not/alternatives treatment.

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

A4.3/5.0
Disambiguation4/5

Most tools target a distinct resource and action — search vs. saved-library synthesis vs. citation analysis vs. article metadata — and the descriptions explicitly cross-reference one another to reduce confusion. A few retrieval/analysis tools (get_field_orientation, get_foundational_lineage, get_citations, check_drift) have adjacent purposes and could be misselected without reading their descriptions carefully.

Naming Consistency4/5

The overwhelming majority follow a clear verb_noun snake_case pattern: create_watch, delete_watch, list_library, save_paper, annotate_paper, fetch_fulltext, search_papers. Minor deviations like co_author_graph and the interchangeable retrieval verbs (search, find, get, check, ask) create slight inconsistency, but the overall convention is predictable.

Tool Count3/5

27 tools is on the heavy side, but the server covers several coherent subdomains: search/discovery, library/collection management, watches, annotations, and research analysis. The count is justifiable for the broad purpose, though some of the discovery/analysis tools could likely be consolidated or split into a separate server.

Completeness4/5

The tool surface covers the core lifecycle well: search, fetch, save, organize into collections, annotate, watch for new papers, and analyze citations/authors/gaps. Minor gaps exist — there is no collection deletion/rename, no explicit mark-as-read tool, and no unlike operation — but these are workable edge cases rather than blocking omissions.

Resources