Load Relevant Entities from the Bstack Knowledge Graph (research/entities/) for a Given
Load relevant entities from the bstack knowledge graph (research/entities/) for a given topic. Two-tier scoring: tier-1 (catalog-only, ~5ms — slug + tags + claim + links + sources match against docs/knowledge-index.md) is the fast first pass and the only stage for high-confidence exact-slug/tag queries; tier-2 (body-grep fallback, ~300ms — auto-fires when tier-1 returns < N matches OR its best hit is below the confidence floor, default 18) recovers topics whose vocabulary appears in entity prose but not the dense catalog (hit rate jumps from 70% → 100% on representative queries; this is hit rate ≥1, not true recall@N). Surfaces top-N entity bodies as a single context block the agent reasons over. This is a LOAD skill, not a query DSL — querying is what the agent does once loaded. Implements the LLM-as-index architecture (BRO-1223): substrate canonical, one projection (catalog) routes, agent IS the query engine. Empirical: peak per-query context drops from 29% → 4.6% of 1M (6.3× reduction); cumulative session tokens 23.8× fewer over 10 queries. Default N=10 entities; override with --n. Tier-2 auto-fires on few-OR-weak tier-1 hits (confidence gate, default --tier2-floor 18; BRO-1426 lifts R@5 0.871→0.952, MRR 0.868→0.968 with no flag); force unconditionally with --body-search, disable the gate with --tier2-floor 0. Routing-quality flags (BRO-1422): --terms (query expansion — score agent-supplied synonyms/variants alongside the topic), --expand 1 (graph 1-hop — also load related: neighbours of top hits, capped at --n extra, total ≤ 2x--n), --explain (per-signal score trace); hub-aware tiebreak always on. Output: catalog header + ranked entity blocks with full body. USE WHEN load knowledge graph, kg load, load entities, route to entities, load context for, what do we know about, what entities are relevant to, surface knowledge on, browse the graph for, find entities about, semantic load, topical load, agent-as-index load. NOT FOR PAI session retrieval (use ContextSearch), web research (use Research), Knowledge Archive ingest (use Knowledge), or entity write/edit operations (those are direct Read+Edit + commit per the AGENTS.md §P6 sub-rule on substrate-edit-as-inference-persistence).
Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI
Supported by the Atlas install prompt. Skill-specific requirements vary.
Skill stats
Skills1CategoryScience & researchStars0
About this skill
Load relevant entities from the bstack knowledge graph (research/entities/) for a given topic. Two-tier scoring: tier-1 (catalog-only, ~5ms — slug + tags + claim + links + sources match against docs/knowledge-index.md) is the fast first pass and the only stage for high-confidence exact-slug/tag queries; tier-2 (body-grep fallback, ~300ms — auto-fires when tier-1 returns < N matches OR its best hit is below the confidence floor, default 18) recovers topics whose vocabulary appears in entity prose but not the dense catalog (hit rate jumps from 70% → 100% on representative queries; this is hit rate ≥1, not true recall@N). Surfaces top-N entity bodies as a single context block the agent reasons over. This is a LOAD skill, not a query DSL — querying is what the agent does once loaded. Implements the LLM-as-index architecture (BRO-1223): substrate canonical, one projection (catalog) routes, agent IS the query engine. Empirical: peak per-query context drops from 29% → 4.6% of 1M (6.3× reduction); cumulative session tokens 23.8× fewer over 10 queries. Default N=10 entities; override with --n. Tier-2 auto-fires on few-OR-weak tier-1 hits (confidence gate, default --tier2-floor 18; BRO-1426 lifts R@5 0.871→0.952, MRR 0.868→0.968 with no flag); force unconditionally with --body-search, disable the gate with --tier2-floor 0. Routing-quality flags (BRO-1422): --terms (query expansion — score agent-supplied synonyms/variants alongside the topic), --expand 1 (graph 1-hop — also load related: neighbours of top hits, capped at --n extra, total ≤ 2x--n), --explain (per-signal score trace); hub-aware tiebreak always on. Output: catalog header + ranked entity blocks with full body. USE WHEN load knowledge graph, kg load, load entities, route to entities, load context for, what do we know about, what entities are relevant to, surface knowledge on, browse the graph for, find entities about, semantic load, topical load, agent-as-index load. NOT FOR PAI session retrieval (use ContextSearch), web research (use Research), Knowledge Archive ingest (use Knowledge), or entity write/edit operations (those are direct Read+Edit + commit per the AGENTS.md §P6 sub-rule on substrate-edit-as-inference-persistence).
Quick start
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Load relevant entities from the bstack knowledge graph (research/entities/) for a given topic. Two-tier scoring: tier-1 (catalog-only, ~5ms — slug + tags + claim + links + sources match against docs/knowledge-index.md) is the fast first pass and the only stage for high-confidence exact-slug/tag queries; tier-2 (body-grep fallback, ~300ms — auto-fires when tier-1 returns < N matches OR its best hit is below the confidence floor, default 18) recovers topics whose vocabulary appears in entity prose but not the dense catalog (hit rate jumps from 70% → 100% on representative queries; this is hit rate ≥1, not true recall@N). Surfaces top-N entity bodies as a single context block the agent reasons over. This is a LOAD skill, not a query DSL — querying is what the agent does once loaded. Implements the LLM-as-index architecture (BRO-1223): substrate canonical, one projection (catalog) routes, agent IS the query engine. Empirical: peak per-query context drops from 29% → 4.6% of 1M (6.3× reduction); cumulative session tokens 23.8× fewer over 10 queries. Default N=10 entities; override with --n. Tier-2 auto-fires on few-OR-weak tier-1 hits (confidence gate, default --tier2-floor 18; BRO-1426 lifts R@5 0.871→0.952, MRR 0.868→0.968 with no flag); force unconditionally with --body-search, disable the gate with --tier2-floor 0. Routing-quality flags (BRO-1422): --terms (query expansion — score agent-supplied synonyms/variants alongside the topic), --expand 1 (graph 1-hop — also load related: neighbours of top hits, capped at --n extra, total ≤ 2x--n), --explain (per-signal score trace); hub-aware tiebreak always on. Output: catalog header + ranked entity blocks with full body. USE WHEN load knowledge graph, kg load, load entities, route to entities, load context for, what do we know about, what entities are relevant to, surface knowledge on, browse the graph for, find entities about, semantic load, topical load, agent-as-index load. NOT FOR PAI session retrieval (use ContextSearch), web research (use Research), Knowledge Archive ingest (use Knowledge), or entity write/edit operations (those are direct Read+Edit + commit per the AGENTS.md §P6 sub-rule on substrate-edit-as-inference-persistence).
About this listing
Category
Science & research
Reported license
MIT
Listing language (estimated)
English
Review status
Not individually reviewed
Agent compatibility
Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.
Claude Code
Codex
Cursor
GitHub Copilot
Gemini CLI