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YGao2005

Scholar Feed MCP Server

Create Watch

create_watch

Create a standing watch that evaluates new papers daily against your criteria and surfaces matches through email digest and check_watches.

Instructions

Create a standing watch — evaluated daily against newly-indexed papers, surfacing new matches via the email digest and via check_watches. MUTATES. Get-or-create by name (re-creating with an existing name returns it unchanged — never errors on duplicate). TWO forms: (1) the v2 STRUCTURED filter via criteria (collections/authors/categories/text/has_code/min_novelty/similar, AND-composed) — the composable, agent-tunable form, recommended; tune it with preview_watch first, and edit later with update_watch. Structured watches rank by 'rising' (forecasted breakout impact) by default, and tighten with min_impact_pct for an anti-noise watch that surfaces only the breakout papers in your niche. (2) a single legacy seed selector (q OR collection_name OR collection_id OR anchor_paper_id); if criteria is given it takes precedence. Requires SF_API_KEY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesLabel for the watch, e.g. 'novel KV-cache work'.
novelty_minNoOnly surface papers at/above this novelty score (0..1). The signal/noise knob — raise it for 'only tell me when it matters'. Default 0.5.
qNoSemantic/keyword topic seed. One seed selector only.
collection_nameNoWatch the neighborhood of a collection by name (resolved by the backend). One seed selector only.
collection_idNoWatch the neighborhood of a collection by UUID. One seed selector only.
anchor_paper_idNoWatch papers similar to this arXiv ID. One seed selector only.
scope_to_citations_ofNoWatch new papers citing this arXiv ID. One seed selector only.
author_idNoWatch an author's new work, by author ID. One seed selector only.
categoryNoWatch an arXiv category (e.g. 'cs.LG'), filtered by novelty_min. One seed selector only.
criteriaNov2 STRUCTURED filter (collections/authors/categories/text/has_code/min_novelty/similar). When provided, this defines the watch (kind='filter') and the single-selector seeds above are IGNORED. This is the composable, agent-tunable form — call preview_watch first to tune it.
recency_daysNoFor a structured (criteria) watch: only consider papers from the last N days (default 7; the 'cites' relation uses 30).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okNoTrue when the operation succeeded.
messageNoHuman-readable summary of the outcome.
actionNoMachine label: saved | no_change | removed | liked | created | updated | deleted.
arxiv_idNo
collectionNoThe created/affected collection, when applicable.
watchNoThe created/affected watch, when applicable.
Behavior5/5

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

Annotations indicate mutation (readOnlyHint=false) and non-destructive (destructiveHint=false). The description explicitly states 'MUTATES' and explains idempotency via get-or-create by name. It also discloses daily evaluation, email digest integration, and requirement for SF_API_KEY, providing full behavioral context beyond annotations.

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?

The description is well-structured with clear segments, bullet points, and front-loaded purpose. While somewhat lengthy, the complexity of the tool (11 parameters, nested objects) justifies the length. Every sentence adds value, and the structure aids readability.

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?

Given the tool's complexity, the description covers purpose, behavior, prerequisites (API key), forms, idempotency, and references to sibling tools. The input schema has full parameter descriptions, and an output schema exists. No gaps remain for an agent to make informed decisions.

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 covers 100% of parameters with individual descriptions. The description adds significant value by explaining the relationship between criteria and single-selector seeds, detailing the collections relation (e.g., similar floor notes), and providing strategic usage hints. However, most parameter meaning is already in the schema, so the incremental value is moderate.

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 creates a standing watch that is evaluated daily and surfaces matches via email and check_watches. It specifies the verb ('create'), resource ('watch'), and scope ('standing watch evaluated daily'), distinguishing it from sibling tools like update_watch, delete_watch, and check_watches.

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 provides explicit guidance on when to use the tool, including two forms (v2 structured vs legacy), recommending structured form, advising preview_watch before creation, and noting get-or-create behavior. It mentions alternatives like update_watch and preview_watch, but does not systematically list all when-not scenarios (e.g., if you only need to read, use list_watches). Still, it offers substantial contextual guidance.

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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