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/tokf-discover

Find missed token savings in Claude Code sessions and create filters for unfiltered commands

From plugin
tokf
1924 skills1 command
Install
$ npx -y skills add mpecan/tokf --skill tokf-discover --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/tokf-discover

Context preview

The summary Claude sees to decide when to auto-load this skill.

Find missed token savings in Claude Code sessions and create filters for unfiltered commands

SKILL.md

tokf-discover.SKILL.md
name: tokf-discover
description: Find missed token savings in Claude Code sessions and create filters for unfiltered commands
user_invocable: true

tokf discover — Find Missed Token Savings

Use this skill to analyze Claude Code sessions and find commands that are running without tokf filtering, wasting tokens on verbose output.

Quick Start

Run `tokf discover` in the project directory to scan recent sessions:

tokf discover

Options

  • `--all` — scan all projects, not just the current one
  • `--since 7d` — only scan sessions from the last 7 days (also `24h`, `30m`)
  • `--limit 0` — show all results (default: top 20)
  • `--json` — output as JSON for programmatic use
  • `--session <path>` — scan a specific session file
  • `--project <path>` — scan sessions for a specific project path

Interpreting Results

The output shows:

  • **COMMAND** — the shell command pattern being run without filtering
  • **FILTER** — the tokf filter that would handle it
  • **RUNS** — how many times it appeared in sessions
  • **TOKENS** — estimated token count of unfiltered output
  • **SAVINGS** — estimated tokens that filtering would save

Workflow

1. Run `tokf discover` to identify top savings opportunities 2. For commands with existing filters: run `tokf hook install` to set up automatic filtering 3. For commands without filters: use `/tokf-filter` skill to create a custom filter 4. Re-run `tokf discover` after changes to verify improvement

Creating Filters for Unfiltered Commands

If `tokf discover` shows commands with no matching filter, create one:

# See what a filter would look like
tokf which "the-command --args"

# Use the tokf-filter skill to create a proper filter
# /tokf-filter

JSON Output

Use `--json` for integration with other tools:

tokf discover --json | jq '.results[] | select(.estimated_savings > 1000)'

The JSON schema includes:

  • `sessions_scanned` — number of JSONL files processed
  • `total_commands` — all Bash commands found
  • `already_filtered` — commands already using tokf
  • `filterable_commands` — commands with available filters
  • `no_filter_commands` — commands with no matching filter
  • `estimated_total_savings` — total estimated token savings
  • `results[]` — per-command breakdown sorted by savings
Read more
Ships withtokf

tokf.net — reduce LLM context consumption from CLI commands by 60–90%. Commands like git push, cargo test, and docker build produce verbose output packed with progress bars, compile noise, and boilerplate.

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Rust
Language
MIT
License
8h ago
Last commit
5mo ago
Created

Repo: mpecan/tokf