Reading List

Researcher Reading List

Build a curated reading list for a researcher, organized by intellectual thread, by triangulating off their most representative recent and most-cited work.

Input

The user provides an author name (e.g., "David W. Hogg", "Yoshua Bengio", "Jennifer Doudna").

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: Verify the author exists

Call get_author_profile with:

• author (string): the author name provided by the user

If no results are found, tell the user the author was not found and suggest checking the spelling or trying a partial name. Stop here.

Note the author's top categories from this result — you'll use them later to interpret which themes the reading list is covering. Also note the resolved author name (resolved_name) — use it consistently in subsequent calls and when filtering self-citations.

Step 2: Get top-cited papers (career anchors)

Call search_by_author with:

• author (string): the author name
• limit (integer): 5
• sort_by (string): "citations"
• strict_mode (string): "fuzzy"

These are the author's most influential works — they anchor the "what defined their career so far" threads.

Step 3: Get recent papers (current direction)

Call search_by_author with:

• author (string): the author name
• limit (integer): 5
• sort_by (string): "relevance"
• strict_mode (string): "fuzzy"

The default relevance sort orders by recency. These represent the author's current intellectual direction, which may differ from their most-cited work.

Step 4: Select 3–5 representative seed papers

From the combined Step 2 + Step 3 results, select 3 to 5 seed papers that best represent the author's distinct intellectual threads:

• Always include the single most-cited paper (career anchor).
• Always include the most recent paper that has a substantive abstract (current direction).
• Fill the remaining slots by picking papers whose category lists differ — i.e. cover different threads of the author's work, not five papers in the same subfield.

If two papers have nearly identical category lists and similar topics, pick only one.

Step 5: Find similar papers for each seed

For each seed paper from Step 4, call find_similar_papers with:

• paper_id (string): the seed paper's ID
• limit (integer): 10
• include_abstract (boolean): false

If a seed paper has no embedding and the call returns an error, skip that seed and continue with the others. Note the skip in the output.

Step 6: Aggregate and clean

After all find_similar_papers calls complete:

1. Tag each result with the seed paper that surfaced it.
2. Deduplicate — if a paper appears in multiple seeds' similar lists, keep the entry with the highest similarity score and merge the seed tags.
3. Filter out self-citations — drop any paper whose author list contains the focal author (use the resolved_name from Step 1 to match, since name normalization may matter).
4. Group by seed — partition the cleaned results by which seed paper(s) surfaced them. This grouping defines the reading-list "threads."

Output Format

Researcher Summary

A short block:

• Name: full name as it appears in the corpus
• Total papers: from Step 1
• Primary domains: top 3 categories from Step 1

Reading List by Thread

For each seed paper from Step 4, produce a thread section:

Thread N:

Anchored by the seed paper:

• Seed: Title (paper ID), year, categories

Recommended reading (5–8 papers per thread, ordered by similarity score):

1. Title (paper ID) — first 3 authors, year, category — one-sentence reason it matters here
2. ...

If a seed paper was skipped because it had no embedding, add a note under that thread: "This seed had no embedding; no similar papers could be retrieved."

Cross-Thread Highlights

If any paper appeared as similar to multiple seeds, highlight it as a cross-thread find — these are often the most interesting recommendations because they sit at the intersection of the author's threads:

• Title (paper ID) — surfaced by Seed A and Seed C — why this matters

If no cross-thread papers were found, omit this section.

Suggested Follow-ups

• /valency:profile <author> — for any author that appears across multiple recommendations
• /valency:similar <paper_id> — to dig deeper into any specific recommendation
• /valency:fresh-collaborators <author> — if the user is interested in who (not what) to engage with next