agentic-graph-rag-skills

In the author's own words, from each skill's SKILL.md — showing the first 30 of 51 files.

• dual-graph-router

  Route an incoming request to the VERTICAL knowledge graph (what the agent knows — a single relationship/temporal traversal), the HORIZONTAL workflow graph (how the agent acts — a decomposed multi-step process), BOTH (a workflow whose nodes query the knowledge graph and write results back), or UNROUTABLE (neither fits — ask for clarification). Implements the central dual-graph distinction of Agent…

  skills/architecture/dual-graph-router/SKILL.md on GitHub (opens in a new tab)

• eight-pillar-readiness-map

  Map an agentic-graph system's current capabilities across the eight pillars of Agentic GraphRAG Ch2 (knowledge representation, memory, reasoning, planning, tool orchestration, structured output, self-evolution, optimization), respect the chapter's layering (each pillar depends on the ones before it), flag dependency violations (a higher pillar claimed present while a lower one it requires is miss…

  skills/architecture/eight-pillar-readiness-map/SKILL.md on GitHub (opens in a new tab)

• harness-node-splitter

  Split a workflow description into constrained harness nodes using the chapter's rule "nodes differ by tool surface, not by prompt." Given candidate operations each with a declared tool set, merge the ones whose tool surfaces overlap >= 80% (prompt variations of one role) and split the ones with distinct tool surfaces (different roles), then emit the per-node constrained context scope the harness…

  skills/architecture/harness-node-splitter/SKILL.md on GitHub (opens in a new tab)

• agent-constraint-triangle-scorer

  Score an agent configuration against Ch1's Agent Constraint Triangle — the three interconnected constraints (complexity management, tool orchestration, context utilization) that make agent design an inherently difficult operational problem. Given the agent's reasoning-chain length, tool-catalog size and disambiguity, and context budget vs. usage, produce a 0-100 pressure score and band per constr…

  skills/crisis/agent-constraint-triangle-scorer/SKILL.md on GitHub (opens in a new tab)

• context-failure-classifier

  Classify an observed agent symptom into Ch1's context-failure taxonomy. Given a sentence describing what an agent did wrong, name the agent-level failure mode (action blindness / memory fragmentation / planning paralysis / context drift / tool chaos), the architectural root cause among the five fatal flaws, and the curing graph capability. Batch mode aggregates a post-mortem's symptoms into a pri…

  skills/crisis/context-failure-classifier/SKILL.md on GitHub (opens in a new tab)

• enterprise-readiness-scorer

  Score a proposed or deployed enterprise agent against the architectural requirements Ch1 argues are non-negotiable: absence of the five fatal flaws of naive vector RAG (context amnesia / relationship blindness / temporal ignorance / reasoning paralysis / tool chaos), calibration of the three agency dimensions (autonomy / action / authority), presence of the four emergent capabilities, and the dec…

  skills/crisis/enterprise-readiness-scorer/SKILL.md on GitHub (opens in a new tab)

• vector-vs-graph-retrieval-selector

  Recommend VECTOR / GRAPH / HYBRID retrieval for a query workload, grounded in Ch1's BenchmarkQED evidence for where vector RAG succeeds and where it collapses. Classifies the workload on the BenchmarkQED scope x type axes (local/global, data/activity), weighs multi-hop / temporal / associativity needs, domain structure, corpus scale, and latency, then returns a recommendation with the chapter's n…

  skills/crisis/vector-vs-graph-retrieval-selector/SKILL.md on GitHub (opens in a new tab)

• workflow-agent-spectrum-classifier

  Place an AI system on Ch1's continuous workflow-agent spectrum instead of the false binary "is it an agent or not". Scores the three dimensions of agency (autonomy / action / authority) plus how predefined the execution path is, returns a spectrum position (0 = workflow, 1 = agent) and a band (WORKFLOW / BLENDED / AGENT), applies Ch1's action test (a system that cannot effect change is an assista…

  skills/crisis/workflow-agent-spectrum-classifier/SKILL.md on GitHub (opens in a new tab)

• capability-authorization-gate

  Runtime authorization gate built on the Ch3 Capability Model Pattern — a self-aware agent represents its own capabilities, required resources/grants, authorization level, and quantitative limits as queryable structure, then checks at PLANNING time whether it may perform an action BEFORE attempting it. Returns allow, escalate (the agent itself cannot but a higher authority could — route appropriat…

  skills/knowledge-representation/capability-authorization-gate/SKILL.md on GitHub (opens in a new tab)

• entity-resolution-strategy-selector

  Choose HOW to decide when two records are the same real-world entity — EVIDENCE-BASED resolution (deterministic feature-by-feature scoring with explainable evidence and culturally-robust rules) vs GENERALIZATION-BASED AI (LLM statistical similarity, nondeterministic, post-hoc rationalization) — per Ch3 "Entity Resolution: The Foundation of Agent Knowledge". Scores a six-factor requirement profile…

  skills/knowledge-representation/entity-resolution-strategy-selector/SKILL.md on GitHub (opens in a new tab)

• graph-model-selector

  Select a graph data model — labeled property graph (LPG) vs RDF vs hypergraph — by scoring REASONING REQUIREMENTS against five implementation features (formal reasoning, n-ary relations, performance, tool ecosystem, constraint expressiveness), per Ch3 "Evaluating Graph Models". Also models the n-ary -> hyperedge representation (Example 3-1: a prescription connecting doctor + patient + medication…

  skills/knowledge-representation/graph-model-selector/SKILL.md on GitHub (opens in a new tab)

• homoiconic-meta-schema

  Homoiconic knowledge representation (Ch3) — code and data share the same representation so an agent can inspect and modify its own knowledge structures with the same machinery it uses for regular data. Two constructs: (1) meta- knowledge structures (Example 3-6) — validate an entity-type against the metaschema AND a data instance against its entity-type using the SAME validator at both levels; (2…

  skills/knowledge-representation/homoiconic-meta-schema/SKILL.md on GitHub (opens in a new tab)

• kg-extraction-approach-selector

  Select a knowledge-graph EXTRACTION approach for a given source — structured database integration vs LLM-based triple extraction vs iText2KG (incremental) vs RAKG (document-level) — by scoring a SOURCE PROFILE against five features (handles unstructured text, incremental-friendly, document-level context, determinism, setup cost), per Ch3 "Extraction Approaches for Heterogeneous Sources". A struct…

  skills/knowledge-representation/kg-extraction-approach-selector/SKILL.md on GitHub (opens in a new tab)

• knowledge-organization-classifier

  Classify an organizational vocabulary onto the Ch3 knowledge-organization spectrum — pick list -> taxonomy -> thesaurus -> ontology — by the structural features the spec actually exhibits, walking bottom-up so a partial ontology does NOT over-claim. Also validates that something claiming to be an ontology carries the five core components the chapter names (classes, subclasses, individuals, axioms…

  skills/knowledge-representation/knowledge-organization-classifier/SKILL.md on GitHub (opens in a new tab)

• schema-pattern-selector

  Select and validate the four agent schema design patterns from Ch3 — Event-Centric (temporal reasoning), Contextual-Boundary (scope/validity boundaries), Multi-Perspective (contradictory viewpoints with attribution and confidence), and Capability-Model (agent self-awareness of authority limits). Given a free-text description of a knowledge shape, it scores which pattern(s) fit and flags compositi…

  skills/knowledge-representation/schema-pattern-selector/SKILL.md on GitHub (opens in a new tab)

• three-graph-router

  Route an incoming record/fact into the correct graph of the Three-Graph Architecture (Ch3) — DOMAIN (trusted, entity-resolved single source of truth), LEXICAL (verbatim source text with provenance, the "retrieval" in RAG), or SUBJECT (LLM-extracted artifacts kept SEPARATE from domain until entity resolution links them). The router enforces the boundaries that make the architecture work — an extra…

  skills/knowledge-representation/three-graph-router/SKILL.md on GitHub (opens in a new tab)

• bi-temporal-edge

  Bi-temporal edge primitive for agentic graph memory. Tracks two independent time dimensions per relationship: when the relationship was VALID in the domain (valid_from / valid_until) and when the system LEARNED about it (ingested_at). Enables point-in-time queries like "What was the EC2 instance type for service-checkout-api at 2026-03-15T08:00Z when the outage occurred?" — answerable even after…

  skills/memory/bi-temporal-edge/SKILL.md on GitHub (opens in a new tab)

• graphiti-incremental-update

  Graphiti (Zep) incremental-update pattern (Ch4). When new content arrives, process only the new content — never re-process the entire graph. Pipeline: (1) extract entities from new episode, (2) entity-resolve against existing graph (dedupe by canonical name + alias + fuzzy match), (3) incremental- update — touch only the affected neighborhood, leave the rest of the graph unchanged. Keeps update l…

  skills/memory/graphiti-incremental-update/SKILL.md on GitHub (opens in a new tab)

• hierarchical-memory

  Three-tier hierarchical memory (Letta / MemGPT pattern) — core / recall / archival. Core holds a small, fast, frequently-accessed working set (e.g. core_limit=2000 tokens). Recall holds raw interaction history for "what did we talk about yesterday" questions. Archival holds effectively unlimited overflow, still searchable. Make forgetting and archiving explicit design choices, not afterthoughts.…

  skills/memory/hierarchical-memory/SKILL.md on GitHub (opens in a new tab)

• hindsight-epistemic-classifier

  Classify facts into HINDSIGHT's 4 epistemic networks (Latimer et al. 2025, cited in Ch4): World (objective external facts), Experience (agent's own first-person actions), Opinion (subjective beliefs with confidence), and Observation (synthesized entity summaries). The separation enables traceability — when users ask "how do you know that", the agent can distinguish evidence from inference from su…

  skills/memory/hindsight-epistemic-classifier/SKILL.md on GitHub (opens in a new tab)

• letta-failure-modes

  Reviewer skill: diagnose an agent's memory architecture against the 8 Letta Leaderboard failure modes (Ch4). Takes a memory snapshot (or a description of the architecture) and reports which failure modes are present, with concrete evidence and recommended fixes. Use BEFORE shipping any memory implementation to production and BEFORE root-causing why a deployed agent "forgets" or "drifts." NOT a be…

  skills/memory/letta-failure-modes/SKILL.md on GitHub (opens in a new tab)

• memory-consistency-model-selector

  Choose a memory consistency model PER agent-coordination operation — STRONG (linearizable), CAUSAL, READ-YOUR-WRITES, or EVENTUAL — by scoring the operation's requirements (shared authoritative state, conflict intolerance, staleness budget, collaboration, self-session continuity), per Ch4 "Memory consistency models for agent coordination". The chapter's rule: default to causal, escalate to strong…

  skills/memory/memory-consistency-model-selector/SKILL.md on GitHub (opens in a new tab)

• memory-consolidation

  Consolidation pipeline — turn noisy raw episodes into durable knowledge (Agentic GraphRAG Ch4, Example 4-5 + Example 4-13). Four steps: cluster related episodes by topic, summarize each cluster into one consolidated fact, create the consolidated node, and maintain a provenance chain back to the source episodes so "how do you know that?" is answerable. Clusters below a minimum size (default 3) are…

  skills/memory/memory-consolidation/SKILL.md on GitHub (opens in a new tab)

• rrf-hybrid-retrieval

  Reciprocal Rank Fusion (RRF) hybrid retrieval across 4 parallel channels — semantic / keyword / graph-traversal / temporal — followed by cross-encoder rerank and token-budget filter (HINDSIGHT, Latimer et al. 2025, cited in Ch4). Rank-based fusion means scores don't need calibration across channels; absent items contribute nothing; items high in multiple lists surface naturally. Use when memory m…

  skills/memory/rrf-hybrid-retrieval/SKILL.md on GitHub (opens in a new tab)

• cost-performance-scorer

  Score a multi-model routing policy on cost versus quality using the two metrics that actually decide selective intelligence: cost per successful completion (not cost per token) and a per-node quality parity threshold with domain-specific failure weights. Wraps a NodeInvocation log, computes cost-per-success and p95 latency per node, and evaluates a candidate model against a per-node evaluation se…

  skills/optimization/cost-performance-scorer/SKILL.md on GitHub (opens in a new tab)

• kv-cache-latency-budgeter

  Budget a specialist model fleet against the two production bottlenecks: KV-cache-bound concurrency and end-to-end latency. Computes how many concurrent users a GPU can host (peak KV per active user, not model size, is the binding constraint), proves that quantizing weights does not move that ceiling while KV compression (MEMENTO) does, estimates GPU speedups for graph analytics (cuGraph / nx-cugr…

  skills/optimization/kv-cache-latency-budgeter/SKILL.md on GitHub (opens in a new tab)

• model-routing-selector

  Match model capability to task complexity across a horizontal workflow graph. Given a node, pick the cheapest model that meets its quality bar, using one of three routing strategies: static routing by node type, threshold-based cascading (FrugalGPT), or learned routing (RouteLLM / MixLLM). Re-derives the book's DevOps DEVOPS_MODEL_CONFIG from first principles and reports the blended cost reductio…

  skills/optimization/model-routing-selector/SKILL.md on GitHub (opens in a new tab)

• schema-evolution-migrator

  Keep a production knowledge graph healthy across schema evolution, node/edge lifecycle, incremental updates, and coordinated deployment. Emits N-1 compatible Neo4j-Migrations-style schema migrations, temporal-invalidation Cypher (bitemporal t_valid/t_invalid, invalidate-not-delete), LightRAG-style incremental merge from a deployment event, TTL/retention policy per node class, and a four-phase sta…

  skills/optimization/schema-evolution-migrator/SKILL.md on GitHub (opens in a new tab)

• subgraph-access-control

  Scope what each agent persona can see in a knowledge graph. Generates Neo4j fine-grained GRANT/DENY policy (traverse on node labels + relationship types, read on properties) per persona role, enforces security transparency (out-of-scope nodes are invisible, not access-denied), handles PII via the UUID-separation pattern with GDPR soft/hard erasure, and turns the Chapter-7 execution graph into a c…

  skills/optimization/subgraph-access-control/SKILL.md on GitHub (opens in a new tab)

• constraint-guided-plan-validator

  Validate a generated plan against extracted domain constraints AND the agent's capability model before execution (Ch5 Constraint-guided planning, Example 5-14, plus the DevOps hypothesis-formation capability filter). Scores the plan 0..1, returns structured per-step feedback so a planning node can refine when the score falls below threshold, and filters steps the agent is not authorized to perfor…

  skills/reasoning-planning/constraint-guided-plan-validator/SKILL.md on GitHub (opens in a new tab)

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