Unnamed Skill
Persistent graph-based memory for AI agents via KIP (Knowledge Interaction Protocol). Provides structured knowledge storage (concepts, propositions), retrieval (KQL queries), schema discovery (META), and memory metabolism. Use when: (1) remembering user preferences, identities, or relationships across sessions, (2) storing conversation summaries or episodic events, (3) building and querying knowledge graphs, (4) the user says "remember this", "what do you know about me", or asks about past conversations, (5) needing to maintain context continuity across sessions. Requires HTTP access to a KIP backend (anda_cognitive_nexus_server).
$ Instalar
git clone https://github.com/ldclabs/KIP /tmp/KIP && cp -r /tmp/KIP/skill/kip-cognitive-nexus ~/.claude/skills/KIP// tip: Run this command in your terminal to install the skill
name: kip-cognitive-nexus description: Persistent graph-based memory for AI agents via KIP (Knowledge Interaction Protocol). Provides structured knowledge storage (concepts, propositions), retrieval (KQL queries), schema discovery (META), and memory metabolism. Use when: (1) remembering user preferences, identities, or relationships across sessions, (2) storing conversation summaries or episodic events, (3) building and querying knowledge graphs, (4) the user says "remember this", "what do you know about me", or asks about past conversations, (5) needing to maintain context continuity across sessions. Requires HTTP access to a KIP backend (anda_cognitive_nexus_server).
KIP Cognitive Nexus
You have a Cognitive Nexus (external persistent memory) via the execute_kip.py script.
Quick Start
python scripts/execute_kip.py --command 'DESCRIBE PRIMER'
Core Operations
Query (KQL)
FIND(?p.name, ?p.attributes.handle) WHERE { ?p {type: "Person"} } LIMIT 10
Store (KML)
UPSERT {
CONCEPT ?e {
{type: "Event", name: "conv:2025-01-01:topic"}
SET ATTRIBUTES { event_class: "Conversation", content_summary: "..." }
SET PROPOSITIONS { ("belongs_to_domain", {type: "Domain", name: "Projects"}) }
}
}
WITH METADATA { source: "conversation", author: "$self", confidence: 0.9 }
Schema Discovery (META)
DESCRIBE PRIMER— Global summaryDESCRIBE CONCEPT TYPE "Person"— Type definitionSEARCH CONCEPT "alice"— Fuzzy search
Critical Rules
- Case Sensitivity: Types =
UpperCamelCase, predicates =snake_case - Define Before Use:
DESCRIBEfirst if unsure - SET ATTRIBUTES = Full replacement per key; SET PROPOSITIONS = Additive
Script Usage
Single command:
python scripts/execute_kip.py \
--command 'FIND(?p.name) WHERE { ?p {type: "Person"} } LIMIT 10'
With parameters:
python scripts/execute_kip.py \
--command 'FIND(?p) WHERE { ?p {type: :type} } LIMIT :limit' \
--params '{"type": "Person", "limit": 5}'
Batch commands:
python scripts/execute_kip.py \
--commands '["DESCRIBE PRIMER", "FIND(?t.name) WHERE { ?t {type: \"$ConceptType\"} } LIMIT 50"]'
Dry run (validation only):
python scripts/execute_kip.py \
--command 'DELETE CONCEPT ?n DETACH WHERE { ?n {type: "Event", name: "old"} }' \
--dry-run
Environment variables:
KIP_SERVER_URL: Server endpoint (default:http://127.0.0.1:8080/kip)KIP_API_KEY: Optional Bearer token for authentication
Error Recovery
| Code | Action |
|---|---|
KIP_1xxx | Fix syntax (quotes, braces) |
KIP_2xxx | Run DESCRIBE, correct Type/predicate names |
KIP_3001 | Reorder UPSERT (define handles before use) |
References
- Complete syntax: references/SYNTAX.md
- Agent workflow guide: references/INSTRUCTIONS.md
- Full specification: references/KIP.md
