cortex-navigate-knowledge

A knowledge-graph navigation add-on for exploring how stored entities and memories are connected. A knowledge graph represents relationships between things such as people, technologies, concepts, and files.

In plain words
What is it for?
Use it to trace what caused something, find what connects two entities, explore related topics, and follow paths through groups of stored memories.
Why use it?
It helps answer relationship and cause-and-effect questions by following connected information instead of searching each item separately.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/cdeust/cortex/cortex-navigate-knowledge
Any agent
npx skills add cdeust/Cortex --skill cortex-navigate-knowledge
Clone the repo
git clone --depth 1 https://github.com/cdeust/Cortex

Made for: Claude Code, Codex.

Per session 95 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 780 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00095 $0.00780
Opus 5 $0.00048 $0.00390
Sonnet 5 $0.00019 $0.00156
Haiku 4.5 $0.00010 $0.00078

Measured yesterday against content hash 5b78d8c62153, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

cortex-navigate-knowledge scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/cortex-navigate-knowledge/SKILL.md · 102 lines

How it starts

The opening of the file, as written. The whole thing — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Keywords

knowledge graph, relationships, connections, causal chain, how are these related, what connects, drill down, explore, navigate, entity graph, trace, cause and effect, related to, linked to, co-access, cluster

Overview

Cortex maintains a knowledge graph of entities (people, technologies, concepts, files) and their relationships extracted from memories. This skill lets you traverse that graph — follow causal chains, explore co-access patterns, drill into fractal memory clusters, and understand how different pieces of knowledge connect.

Use this skill when: You need to understand relationships between concepts, trace cause-and-effect chains, or explore a topic area systematically.

Workflow

Step 1: Trace Causal Chains

Follow entity relationships through the knowledge graph:

cortex:get_causal_chain({
  "entity": "PostgreSQL",
  "direction": "both",
  "max_depth": 3
})

Returns a chain of entities connected by typed relationships (causes, uses, depends_on, related_to, etc.). Direction can be "forward" (effects), "backward" (causes), or "both".

Step 2: Navigate Co-Access Paths

Find memories frequently accessed together using Successor Representation:

cortex:navigate_memory({
  "memory_id": <starting_memory_id>,
  "depth": 2,
  "max_nodes": 20
})

Returns a graph of memories connected by co-access frequency — revealing implicit relationships that aren't in the explicit knowledge graph.

Step 3: Hierarchical Exploration

Browse memories through fractal clusters (L0 = broad, L1 = mid, L2 = specific):

cortex:recall_hierarchical({
  "query": "authentication system",
  "levels": 3
})

Then drill into any interesting cluster:

cortex:drill_down({
  "cluster_id": "<cluster from hierarchical recall>",
  "level": "L1"
})

Step 4: Detect Structural Gaps

Find disconnected or under-connected areas:

cortex:detect_gaps({
  "domain": "<optional>"
})

Read the full file on GitHub · 102 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 102 lines · 95 tokens per session scan A 5b78d8c62153

Subscribe to this mod's changes

cortex-navigate-knowledge is a skill published in the GitHub repository cdeust/Cortex (71 stars, last pushed 3d ago), licensed MIT. It adds 95 tokens to every session and 780 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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