Trends

Publication Trends

Show how a topic or category has evolved over time.

Input

The user provides one of:

• An arXiv category code (e.g., cs.LG) — recognized by the short-prefix-dot-suffix pattern
• A keyword or phrase (e.g., "transformer", "CRISPR")
• Multiple categories or keywords separated by commas or "vs" (e.g., "cs.LG, cs.CL" or "transformers vs RNNs") — for comparison

Tool Chain

Use the Valency MCP tools — they come from the valency MCP server registered by the companion Valency connector extension. If no valency server is registered, tell the user to install the connector and run /mcp auth valency. Stop here.

Step 1: Get trend data

If the input is a single category code:

Call get_publication_trends with:

• category (string): the category code
• granularity (string): "year"
• format (string): "compact"

If the input is a single keyword/phrase:

Call get_keyword_trends with:

• query (string): the keyword
• granularity (string): "year"
• format (string): "compact"

If the input contains multiple categories (comma-separated or "vs"):

Call get_publication_trends individually for each category with:

• category (string): each category code
• granularity (string): "year"
• format (string): "compact"

Note: get_publication_trends_batch exists but is unreliable and frequently times out. Use individual calls instead and combine the results into a comparison table.

If the input contains multiple keywords (comma-separated or "vs"):

Call get_keyword_trends once per keyword with:

• query (string): each keyword
• granularity (string): "year"
• format (string): "compact"

Step 2: Get recent representative papers

Call search_by_abstract with:

• query (string): the keyword or category name (use the human-readable name for categories, e.g., "machine learning" for cs.LG)
• limit (integer): 5
• sort_by (string): "relevance"

Output Format

Trend Data

For single input: a year-by-year table:

For comparisons: a side-by-side table:

Narrative Summary

A 3-5 sentence narrative covering:

• When the field or topic first appeared in the corpus
• Key inflection points (years where volume jumped or dropped significantly)
• Current trajectory (accelerating, plateauing, declining)
• For comparisons: which topic is growing faster and when they diverged

Representative Recent Papers

A numbered list of 3-5 papers from Step 2. For each:

• Title (with paper ID)
• Authors (first 3, then "et al.")
• Year

Suggested Follow-ups

• /valency:landscape <category> — for a broader overview of the field
• /valency:profile <author> — for authors driving the trend
• /valency:trends <other_keyword> — to compare with related topics