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Scan an entity's summary/metadata and cross-reference the graph to suggest new edge relationships (FACED, INFLUENCED_BY, LED, RIVALED, MENTORED, etc.) in Apache AGE. Use when the Knowledge Graph agent must enrich the Human Story Graph after a new entity or source is added.
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基于 SOC 职业分类
Query the keyless academic and public-domain registries (OpenAlex, Crossref, Semantic Scholar, Project Gutenberg, Internet Archive, Stack Exchange) for a topic and get back normalized, copyright-safe reference metadata (title, link, provenance). Use when gather-citations or verify-claims needs primary-literature grounding instead of the LLM's training memory.
Query Wikipedia, Wikidata, Stack Exchange, public Discourse forums, academic APIs, and public-domain archives to synthesize facts, human struggles, and philosophical debates to build the narrative arc for a topic. Store only facts/events/dates/relationships, dialogic tension points, and reference metadata — never full articles (copyright-safe pipeline, spec §2.5).
Query Metacritic, GameSpot, and TVGuide (resolved and read via Bright Data) for a personality's existing game/film/TV adaptation, extracting critic/user scores, narrative themes critics highlighted, and reception debates. Use when generate-psych-profile or backlog-ranking want a critical-reception signal on top of gather-citations' facts and fandom-lore's fan interpretation.
Compose the per-beat music score plan (Lyria cues, deliberate silence segments, optional sound-effect cues) for a content run by calling Hermes's music-director judgment agent. Use when the Content Factory agent must produce the music_director_output that Hermes's content-run pipeline needs for music generation, beat-synced editing, and the SFX layer.
Decide the whole-video visual grade, typography, and per-shot treatments (transitions, camera moves, grade deviations, light leaks) for a content run by calling Hermes's visual-director judgment agent. Use when the Content Factory agent must produce the visual_director_output that Hermes's content-run pipeline needs for shot styling in Video Assembly.
Trigger Hermes's deterministic 11-agent video-production pipeline for an editorially-approved run, and poll it to completion. Use when submit-editorial-review records a human PASS and the approved asset bundle is ready to actually produce.
| name | autolink-entities |
| description | Scan an entity's summary/metadata and cross-reference the graph to suggest new edge relationships (FACED, INFLUENCED_BY, LED, RIVALED, MENTORED, etc.) in Apache AGE. Use when the Knowledge Graph agent must enrich the Human Story Graph after a new entity or source is added. |
| metadata | {"agent":"knowledge-graph","source":"Project Atlas Agent Skills Manifest §3","layer":"memory"} |
Propose and write new graph edges for an entity.
INSPIRED, RIVALED, FAILED, REINVENTED, LED, MENTORED, INFLUENCED, ACQUIRED
e.g. (RatanTata)-[:LED]->(TataGroup).
def autolink_entities(entity_id: str) -> list:
"""Cross-reference the graph and return suggested new edges for entity_id."""
entity_id.{from, type, to, confidence}.Call the temporal-bridge MCP tool start_workflow("autolinkEntitiesWorkflow", "knowledge-graph", [{"entity_id": entity_id}]), then poll get_workflow_result(workflow_id). Reads the entity + its existing relationships rows and nearby candidates (via query-semantic-nodes) from the live Railway Postgres graph, then one LLM call proposes typed edges restricted to the vocabulary above (server/src/modules/graph/graph.service.ts's autolinkEntities). Returns suggestions only -- does not write to relationships itself; a human/Curator must approve and persist them separately, per the existing rule below.
entities/relationships tables (live on Railway), not the Apache AGE
extension this skill's description originally assumed -- the spec (sys_graph.spec.md) only requires
node/edge CRUD + vector lookup + edge suggestion, which this schema already satisfies.deepseek-direct/deepseek-chat to read a summary and propose typed edges; the human/Curator approves before persisting. Output schema-only JSON.