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tokenkiller

Reduces token usage across multi-skill agent workflows (search, coding, debugging, testing, docs) using budgets, gating, progressive disclosure, and deduped evidence. Use when the user mentions saving tokens, cost, context length, long logs, large codebases, or when tasks involve multi-step exploration or debugging.

buttonsinger0 installations selon la source☆ 0 Étoiles du dépôt

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

skillhub install buttonsinger/tokenkiller

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

Instructions

TokenKiller (Universal Throttling)

Goal

Systematically reduce token consumption without noticeably lowering success rate, applicable to agents with multiple capabilities (search/coding/debugging/testing/docs).

Task Complexity Assessment

Before setting budgets, assess task complexity:

Complexity Criteria Tool Budget Output Budget
Simple Single file modification, single-point localization, clear requirements ≤3 calls ≤50 lines
Medium Across 2-3 files, needs simple exploration, relatively clear requirements ≤6 calls ≤120 lines
Complex Cross-module refactoring, multi-step debugging, unclear requirements ≤10 calls ≤200 lines

Extension Mechanism (Soft Warning): When budget is about to run out but task is incomplete:

  1. Output warning: [TokenKiller] Budget running low, current progress X/Y, remaining work: ...
  2. Continue execution, but switch to more conservative strategy
  3. User can interrupt or request more detailed output at any time

Default Working Mode (Balanced)

Global Hard Rules (Must Follow)
  • Goal First, Evidence Later: State the goal in one sentence (L0) first, then decide if evidence is needed (L2/L3).
  • Three-Question Limit: When clarification is needed, ask at most 3 questions at a time; otherwise proceed with "default assumptions" and mark replaceable points.
  • Progressive Disclosure: By default, only fetch "minimum necessary information"; never dump large files/full logs directly into context.
  • Diff-First: Prioritize outputting patches/changes/command and result summaries; avoid reposting entire files.
  • Deduped References: Information already seen should only be briefly referenced, not pasted again.
Budget Gate (Budget + Gate)

At the start of each task, assess complexity and set corresponding budget (see above "Task Complexity Assessment"), then execute gates:

  • Tool Call Budget: Set by complexity (Si...

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/buttonsinger/tokenkiller
Version
—
Commit
66a861abd9c512de89c271b178ab8535b2d927ca
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

README

tokenkiller

Reduce token usage for agent workflows (budgets, gating, progressive disclosure, dedupe).

What it is

TokenKiller is a lightweight skill/policy to systematically reduce LLM token usage without noticeably lowering success rate. It is designed for multi-step agent workflows such as:

  • search / exploration
  • coding / refactoring
  • debugging / troubleshooting
  • testing / verification
  • docs / summarization

How it works

Core mechanisms:

  • Dynamic budgets: Assess task complexity first, then apply appropriate budget (simple/medium/complex)
  • Progressive disclosure: pull only the minimum necessary context (avoid big-file/log dumps)
  • L0-L3 information layers: Start with goal (L0), constraints (L1), evidence (L2); only pull full content (L3) when necessary
  • Diff-first outputs: prefer patches and deltas over full-file reposts
  • Deduped evidence: never paste the same content twice; reference it briefly instead
  • Token self-check: periodic review of token consumption patterns
  • Multi-skill collaboration: works alongside other skills as a constraint layer

Key Features

Dynamic Budget Mechanism
Complexity Criteria Tool Budget Output Budget
Simple Single file, clear requirement ≤3 calls ≤50 lines
Medium 2-3 files, some exploration ≤6 calls ≤120 lines
Complex Cross-module, multi-step, unclear ≤10 calls ≤200 lines

When budget runs low but task incomplete, a warning is issued and strategy shifts to more conservative mode.

L3 Pull Triggers

Only pull full content (L3) in these scenarios:

  • Code modification requiring exact indentation/format
  • Config debugging with interdependent settings
  • Error analysis needing complete stack trace
  • User explicitly requests full content
Multi-Skill Priority
  • Functional skills (pdf, xlsx, etc.) take precedence
  • TokenKiller applies as a constraint layer during output
  • User r...

Contenu extrait

SKILL.md
# TokenKiller (Universal Throttling)

## Goal

Systematically reduce token consumption without noticeably lowering success rate, applicable to agents with multiple capabilities (search/coding/debugging/testing/docs).

## Task Complexity Assessment

Before setting budgets, assess task complexity:

| Complexity | Criteria | Tool Budget | Output Budget |
|------------|----------|-------------|---------------|
| Simple | Single file modification, single-point localization, clear requirements | ≤3 calls | ≤50 lines |
| Medium | Across 2-3 files, needs simple exploration, relatively clear requirements | ≤6 calls | ≤120 lines |
| Complex | Cross-module refactoring, multi-step debugging, unclear requirements | ≤10 calls | ≤200 lines |

**Extension Mechanism (Soft Warning)**: When budget is about to run out but task is incomplete:
1. Output warning: `[TokenKiller] Budget running low, current progress X/Y, remaining work: ...`
2. Continue execution, but switch to more conservative strategy
3. User can interrupt or request more detailed output at any time

## Default Working Mode (Balanced)

### Global Hard Rules (Must Follow)

- **Goal First, Evidence Later**: State the goal in one sentence (L0) first, then decide if evidence is needed (L2/L3).
- **Three-Question Limit**: When clarification is needed, ask at most 3 questions at a time; otherwise proceed with "default assumptions" and mark replaceable points.
- **Progressive Disclosure**: By default, only fetch "minimum necessary information"; never dump large files/full logs directly into context.
- **Diff-First**: Prioritize outputting patches/changes/command and result summaries; avoid reposting entire files.
- **Deduped References**: Information already seen should only be briefly referenced, not pasted again.

### Budget Gate (Budget + Gate)

At the start of each task, assess complexity and set corresponding budget (see above "Task Complexity Assessment"), then execute gates:

- **Tool Call Budget**: Set by complexity (Si...
README
# tokenkiller

Reduce token usage for agent workflows (budgets, gating, progressive disclosure, dedupe).

## What it is

TokenKiller is a lightweight skill/policy to systematically reduce LLM token usage **without noticeably lowering success rate**. It is designed for multi-step agent workflows such as:

- search / exploration
- coding / refactoring
- debugging / troubleshooting
- testing / verification
- docs / summarization

## How it works

Core mechanisms:

- **Dynamic budgets**: Assess task complexity first, then apply appropriate budget (simple/medium/complex)
- **Progressive disclosure**: pull only the minimum necessary context (avoid big-file/log dumps)
- **L0-L3 information layers**: Start with goal (L0), constraints (L1), evidence (L2); only pull full content (L3) when necessary
- **Diff-first outputs**: prefer patches and deltas over full-file reposts
- **Deduped evidence**: never paste the same content twice; reference it briefly instead
- **Token self-check**: periodic review of token consumption patterns
- **Multi-skill collaboration**: works alongside other skills as a constraint layer

## Key Features

### Dynamic Budget Mechanism

| Complexity | Criteria | Tool Budget | Output Budget |
|------------|----------|-------------|---------------|
| Simple | Single file, clear requirement | ≤3 calls | ≤50 lines |
| Medium | 2-3 files, some exploration | ≤6 calls | ≤120 lines |
| Complex | Cross-module, multi-step, unclear | ≤10 calls | ≤200 lines |

When budget runs low but task incomplete, a warning is issued and strategy shifts to more conservative mode.

### L3 Pull Triggers

Only pull full content (L3) in these scenarios:
- Code modification requiring exact indentation/format
- Config debugging with interdependent settings
- Error analysis needing complete stack trace
- User explicitly requests full content

### Multi-Skill Priority

- Functional skills (pdf, xlsx, etc.) take precedence
- TokenKiller applies as a constraint layer during output
- User r...

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