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Run npx skillmds@latest add jmagly-ai-writing-guide/profile-graph in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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Is Profile Graph free to use?

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Who published Profile Graph?

jmagly (@jmagly-ai-writing-guide) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Profile Graph by jmagly-ai-writing-guide

Name: Profile Graph
Rating: 4.2 (5 reviews)
Author: jmagly

Profile Graph

Entity-profile graph edges + embedding similarity for a research corpus — profile→REF edges (first-class adjacency, reconciled against the citation graph) and text-embedding researcher similarity + collaboration link-prediction. Completes the

jmagly Updated Sep 10, 2026

File contents

Profile Graph: Edges & Similarity

The graph-integration + embedding pieces of the entity-profile analytics family (centrality, communities, and temporal trajectories ship in profile-metrics, profile-communities, profile-temporal).

profile→REF edges (no extra deps)

aiwg corpus profile-edges
aiwg corpus profile-edges --out reports/profile-edges.txt

Builds the profile→REF edge graph from each PROF-{P,O,G,F,S}'s corpus-refs, as first-class adjacency (byProfile + reverse byRef), reconciled against the citation graph — edges to REFs with no analysis doc are reported as dangling, not kept. Surfaces top profiles by linked-REF count and top REFs by linked-profile count (cross-cutting influence). Preferred over the section9 synthetic documentation/profiles/edges/ files.

Researcher similarity + collaboration prediction (opt-in embeddings)

# Nearest researchers to a profile
aiwg corpus profile-similar --entity PROF-P-gonzalez-joseph --top 10

# Collaboration link-prediction: similar people who have NOT co-authored
aiwg corpus profile-similar --predict-collabs --threshold 0.85

Embeds each person profile from its name + the titles of its corpus-refs (text-embedding via the #1493 backend — opt-in @xenova/transformers), then:

--entity ranks the nearest researchers by cosine similarity.
--predict-collabs surfaces high-similarity pairs that share no corpus-refs (corpus-refs overlap is the co-authorship proxy) — candidate future collaborators. Lower --threshold to surface more (people who already collaborate are correctly excluded, so a high threshold can legitimately return zero).

This is the #1501 "embeddings" slot, implemented via text embeddings rather than a heavy node2vec/graph-embedding stack (operator decision) — one embedding backend across the codebase, composing with aiwg index --semantic (#1493). Without the optional dep it prints an install hint and exits.

Triggers

"profile to REF edges" / "profile edge graph"
"similar researchers" / "researcher similarity"
"predict collaborations" / "collaboration link prediction"

Notes

TS-native: src/artifacts/corpus-tools/profile-edges.ts (port of build_profile_edges.py) + profile-embed.ts (the graph_embeddings.py slot via text embeddings).
node2vec/structural graph embeddings remain a possible future enhancement; the text-embedding approach here covers the researcher-similarity + link-prediction use cases without the heavy ML stack.

---name: profile-graphdescription: Entity-profile graph edges + embedding similarity for a research corpus — profile→REF edges (first-class adjacency, reconciled against the citation graph) and text-embedding researcher similarity + collaboration link-prediction. Completes the---# Profile Graph: Edges & SimilarityThe graph-integration + embedding pieces of the entity-profile analytics family(centrality, communities, and temporal trajectories ship in `profile-metrics`,`profile-communities`, `profile-temporal`).## profile→REF edges (no extra deps)```bashaiwg corpus profile-edgesaiwg corpus profile-edges --out reports/profile-edges.txt```Builds the **profile→REF edge graph** from each PROF-{P,O,G,F,S}'s `corpus-refs`,as first-class adjacency (`byProfile` + reverse `byRef`), reconciled against thecitation graph — edges to REFs with no analysis doc are reported as **dangling**,not kept. Surfaces top profiles by linked-REF count and top REFs by linked-profilecount (cross-cutting influence). Preferred over the section9 synthetic`documentation/profiles/edges/` files.## Researcher similarity + collaboration prediction (opt-in embeddings)```bash# Nearest researchers to a profileaiwg corpus profile-similar --entity PROF-P-gonzalez-joseph --top 10# Collaboration link-prediction: similar people who have NOT co-authoredaiwg corpus profile-similar --predict-collabs --threshold 0.85```Embeds each **person** profile from its name + the titles of its corpus-refs(text-embedding via the #1493 backend — opt-in `@xenova/transformers`), then:- **`--entity`** ranks the nearest researchers by cosine similarity.- **`--predict-collabs`** surfaces high-similarity pairs that share **no** corpus-refs (corpus-refs overlap is the co-authorship proxy) — candidate future collaborators. Lower `--threshold` to surface more (people who already collaborate are correctly excluded, so a high threshold can legitimately return zero).This is the #1501 "embeddings" slot, implemented via text embeddings rather thana heavy node2vec/graph-embedding stack (operator decision) — one embeddingbackend across the codebase, composing with `aiwg index --semantic` (#1493).Without the optional dep it prints an install hint and exits.## Triggers- "profile to REF edges" / "profile edge graph"- "similar researchers" / "researcher similarity"- "predict collaborations" / "collaboration link prediction"## Notes- TS-native: `src/artifacts/corpus-tools/profile-edges.ts` (port of `build_profile_edges.py`) + `profile-embed.ts` (the `graph_embeddings.py` slot via text embeddings).- node2vec/structural graph embeddings remain a possible future enhancement; the text-embedding approach here covers the researcher-similarity + link-prediction use cases without the heavy ML stack.

Frequently asked questions