Context cost tree

Skill HorizonBrute/Horizon_AI_OS/horizon_system/skills_bin/context-cost-tree

Install

npx -y skills add HorizonBrute/Horizon_AI_OS --skill context-cost-tree

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What its author says it does

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Map Claude Code harness context overhead across the ENTIRE AIOS as an ASCII tree — brute-forces every directory under $HORIZON_ROOT, attributes each auto-loaded CLAUDE.md / agents.md / @-import file to the directory it lives in, and reports per-directory, subtree, and grand-total context cost. Use when the user types /context-cost-tree, wants a whole-AIOS context map, or asks where context cost accrues across the tree (as opposed to /context-cost, which measures one path's upward load).

SKILL.md

3.6 KB, as published. Nobody here has run it

Skill: /context-cost-tree

Model preference: #lowcost (per horizon_aios_model_prefs.md; overridable by a prompt directive).

Show, as ASCII-tree art, where harness context overhead lives across the whole AIOS. Where /context-cost answers "what will a session started here load?" (an upward walk from one path), /context-cost-tree brute-forces the whole tree: it walks down from $HORIZON_ROOT, finds every auto-load file (CLAUDE.md, CLAUDE.local.md, agents.md) plus everything they @-import, de-duplicates, and attributes each file to the directory it physically lives in — so you can see at a glance which directories carry the context weight.

Arguments

/context-cost-tree [path]

path — optional; defaults to $HORIZON_ROOT (the whole AIOS). Pass a path to scope the map to a subtree.

Step-by-step execution

Step 1 — Run the mapper

1.1 Run (no path arg needed — it defaults to $HORIZON_ROOT):

python "$HORIZON_SYSTEM/bin/context_cost_tree.py"

To scope to a subtree, pass a path: python "$HORIZON_SYSTEM/bin/context_cost_tree.py" <path>.

1.2 The script prints the ASCII tree directly. Relay it to the user verbatim inside a code block — the tree art and alignment matter.

1.3 For programmatic use, add --json to get {root, directories[], external, total_files, total_kb, total_tokens} instead of the tree.

If the command fails (non-zero exit, missing script, $HORIZON_ROOT unset), report the error clearly and stop. An unset $HORIZON_ROOT means the AIOS environment is not active — tell the user to source their profile or run the AIOS switcher.

Step 2 — Read the output

Each node shows the tokens/KB/file-count for auto-load files physically in that directory, plus a [subtree: N tok] roll-up for structural (pass-through) directories. Directories with no auto-load weight and no weighted descendants are pruned, so the tree highlights where context accrues rather than dumping every folder.

The grand total sums the de-duplicated auto-load fileset inside the root. A separate External line accounts for files pulled in from outside the tree (e.g. ~/.claude imports).

Step 3 — Flag heavy nodes (optional)

If any single directory dominates the total (e.g. a subtree carrying a large share of the tokens), point it out as the first place to trim CLAUDE.md / agents.md / @-imports.

Notes for the executing agent

$HORIZON_SYSTEM and $HORIZON_ROOT must be set. If not, report that the AIOS environment is not active.
Measurement and @-import resolution are reused from context_cost.py (/context-cost's engine) — it is the single source of truth for tokenization and import semantics. Do not reimplement counting; just run context_cost_tree.py and relay its output.
A file @-imported by several CLAUDE.md files is counted once (de-duplicated) and attributed to where it physically lives — so the tree is a map of where the bytes are, not of every place they get pulled into.
Token counts are estimates (chars ÷ 4), same convention as /context-cost.