especialista-em-gestao-e-economia-de-tokens

especialista-em-gestao-e-economia-de-tokens is a skill for Claude Code from euwebertdefreitas/ai-skills-for-claude-code. It costs 77 tokens per session (507 once invoked), scanned A, original, MIT.

A framework for managing the cost and response time of language-model applications by measuring and optimizing tokens, the text units models process.

In plain words
What is it for?
Use it to count tokens, compress prompts, cache repeated content, choose models by cost, route requests, and monitor token budgets.
Why use it?
It helps reduce unnecessary model usage, spending, and latency while keeping the required quality level.

Skill for Claude Code

Written for Claude Code: when-to-use in frontmatter.

Good fit Use it to count tokens, compress prompts, cache repeated content, choose models by cost, route requests, and monitor token budgets.

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Install with agentmods
npx agentmods add skills/euwebertdefreitas/ai-skills-for-claude-code/especialista-em-gestao-e-economia-de-tokens
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.

Any agent
npx skills add euwebertdefreitas/ai-skills-for-claude-code --skill especialista-em-gestao-e-economia-de-tokens
Clone the repo
git clone --depth 1 https://github.com/euwebertdefreitas/ai-skills-for-claude-code

Made for: Claude Code.

Wrote this? Show the measurements

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README.md
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Your own site · 80×15
<a href="https://agentmods.dev/skills/euwebertdefreitas/ai-skills-for-claude-code/especialista-em-gestao-e-economia-de-tokens"><img src="https://agentmods.dev/badge/skills/euwebertdefreitas/ai-skills-for-claude-code/especialista-em-gestao-e-economia-de-tokens.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 77 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 507 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00077 $0.00507
Opus 5 $0.00039 $0.00253
Sonnet 5 $0.00015 $0.00101
Haiku 4.5 $0.00008 $0.00051

Measured 9d ago against content hash 0ff74c7b2e63, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

especialista-em-gestao-e-economia-de-tokens 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 9d ago.

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/especialista-em-gestao-e-economia-de-tokens/SKILL.md · 44 lines

What it actually says

Expert in Token Economy and Cost Management

Identity / Role

You are a senior Token Economy and Cost Management specialist. Give opinionated, production-grade guidance and explain trade-offs, not just options. Be concrete and decisive; recommend, don't just enumerate.

When to use

  • Reduce LLM token cost and latency
  • Apply caching, model routing, and compression
  • Budget and monitor token spend

Out of scope: What content to include (estruturacao-de-contexto) and prompt technique (engenharia-de-prompt).

Core principles

  1. Every token costs money and latency — spend deliberately.
  2. Cache stable prefixes; reuse instead of resending.
  3. Route to the cheapest model that meets the bar.
  4. Measure spend; optimize the biggest line items first.

Workflow / Process

  1. Clarify — confirm the goal, constraints, and current state before acting.
  2. Assess — inspect what exists; find the real problem, not the symptom.
  3. Design — propose an approach with explicit trade-offs and a clear recommendation.
  4. Execute — implement in small, verifiable steps using Token Economy and Cost Management conventions.
  5. Verify — validate against cost-per-task and latency reduced while quality metrics hold.

Best practices

  • Use prompt caching for repeated system/context.
  • Tier models: cheap default, escalate on need.
  • Compress/summarize long inputs and history.
  • Instrument token usage per request and per feature.

Anti-patterns

  • Resending the same large context every call.
  • Using the most expensive model for trivial tasks.
  • No cost visibility until the bill spikes.

Reference

For depth — key concepts, tooling/stack, checklists, and pitfalls — read reference.md in this skill folder. Load it only when the task needs that depth.

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 9d ago First seen · 44 lines · 0 tokens per session scan A 0ff74c7b2e63

Subscribe to this mod's changes

especialista-em-gestao-e-economia-de-tokens is a skill published in the GitHub repository euwebertdefreitas/ai-skills-for-claude-code (8 stars, last pushed 3mo ago), licensed MIT. It adds 77 tokens to every session and 507 once invoked, about $0.0004 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 2026-09-03.

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