CCO Tools — what your tools really cost

SkillAI & models

Show what tools actually cost in tokens, learned per-tool averages from observed results, replacing the hardcoded MCP/Agent guesses

Use CCO Tools — what your tools really cost in Claude, ChatGPT or Ahel Desktop

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Also: Claude Code · Cursor · Codex

Then ask your AI: use the CCO Tools skill

Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

CCO Tools — what your tools really costStart free

What this skill tells your AI

The instructions your AI receives, as published by egorfedorov/claude-context-optimizer in skills/cco-tools/SKILL.md and read by Ahel’s review.

MCP and Agent token costs used to be constants picked once (mcp__* ≈ 200 in, Agent ≈ 500). Real results vary by orders of magnitude — a "list all issues" query and a one-row lookup are the same tool name and nowhere near the same cost. On MCP-heavy sessions the budget meter was guessing at its biggest line item.

CCO now measures every tool result and learns the average per tool name.

Run from the plugin root:

show (or no arguments)

node ${CLAUDE_PLUGIN_ROOT}/src/tool-costs.js

Prints the learned table: calls, average, worst case, and cumulative total per tool, sorted by total spend.

When reading it back to the user, the useful observations are:

  • The top row by total is where their context budget actually goes. It is frequently an MCP server rather than file reads.
  • A row marked · has fewer than 3 samples and is still using the built-in constant — its estimate isn't trustworthy yet.
  • A large gap between avg and max means that tool is unpredictable; suggest narrowing its queries (filters, limits, pagination) rather than dropping it.

Pair with /cco-overhead mcp — that shows which servers are configured but never called; this shows what the called ones actually cost.

reset

node ${CLAUDE_PLUGIN_ROOT}/src/tool-costs.js reset

Clears the learned table and returns every tool to its built-in constant. Useful after changing MCP servers or their configuration, when past measurements no longer describe the current setup. Confirm before running — the history isn't recoverable.

Signals

GitHub stars
114
Forks
9
Last commit
Sep 2026
Advanced
Item type
skill
Key
cco-tools
Source
github.com/egorfedorov/claude-context-optimizer