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Documentation Index

Fetch the complete documentation index at: https://docs.oktolabs.ai/llms.txt

Use this file to discover all available pages before exploring further.

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Querying the graph

You can query the KG when an agent needs durable context before writing or validating work. Start with specific read tools; use Cypher only when the dedicated tool does not cover the question.

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Natural language queries

okto_pulse_kg_query_natural performs deterministic retrieval over embeddings, HNSW indexes, and traversal. It does not ask an LLM to invent an answer. 
okto_pulse_kg_query_natural(board_id="...", query="why did we choose the current auth model?")

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Cypher queries

okto_pulse_kg_query_cypher is read-only and intended for operators. Use explicit limits and narrow patterns. 
MATCH (d:Decision) RETURN d.title, d.relevance_score LIMIT 20
HNSW indexes cover Decision, Constraint, Requirement, Entity, and Learning nodes. Semantic search is retrieval; it is separate from the stored relevance_score formula.

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Decision history retrieval

Use okto_pulse_kg_get_decision_history when the topic is known but the decision ID is not.

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Contradiction detection

Run okto_pulse_kg_find_contradictions before introducing a spec that may conflict with old decisions or constraints.

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Global cross-board queries

okto_pulse_kg_query_global searches the global discovery graph and respects board access.

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Relevance scoring

The v0.3.3 base score is: 
clamp(0.4*source_confidence + 0.3*log(1+degree)/log(100) + 0.3*decayed_hits - contradict_penalty + priority_boost, 0.0, 1.5)
Bug nodes use the higher of priority boost and severity boost.

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UI boost button

The UI boost endpoint adds +0.3 to stored score and clamps at 1.5. It is an operator override, not a change to semantic retrieval.
Last modified on May 8, 2026