Skills Plugins MCP Prompt Model 博客 我的中心

cost-tracking

Track and report Claude Code token usage, spending, and budgets from the local ECC cost-tracker metrics log. Use when the user asks about costs, spending, usage, tokens, budgets, or cost breakdowns by model, session, or date.

DeepseekModel キュレーション済みスキル 品質 優秀 · 90 v1.0.0

取得

https://deepseekmodel.com/api/download.php?id=affaan-m-ecc-skills-cost-tracking-skill-md&format=skill
ダウンロード .skill 標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能
.skill ファイルの system_prompt フィールドの実際の内容。
name cost-tracking description Track and report Claude Code token usage, spending, and budgets from the local ECC cost-tracker metrics log. Use when the user asks about costs, spending, usage, tokens, budgets, or cost breakdowns by model, session, or date. metadata {"origin":"community"} Cost Tracking Use this skill to analyze Claude Code cost and usage history from the metrics log that ECC's stop:cost-tracker hook writes. Where the data lives The tracker appends one JSON object per session-stop to ~/.claude/metrics/costs.jsonl . Each row is a cumulative snapshot for that session , so to total spend you take the latest row per session_id and sum across sessions — summing every row multiply-counts. Row schema: Field Meaning timestamp ISO timestamp of the snapshot session_id Claude Code session identifier transcript_path Path to the session transcript model Model used input_tokens / output_tokens Token counts cache_write_tokens / cache_read_tokens Prompt-cache token counts estimated_cost_usd Precomputed cumulative cost in USD for the session Prefer estimated_cost_usd over hand-calculating pricing — model and cache prices change, and the tracker is the source of truth. When to Use The user asks "how much have I spent?", "what did this session cost?", or "what is my token usage?" The user mentions budgets, spending limits, overruns, or cost controls. The user wants a cost breakdown by model, session, or date, or a CSV export. How It Works First verify the log exists (use node , not sqlite3 — the tracker writes JSONL, and node is cross-platform): node -e 'const fs=require("fs"),os=require("os"),p=require("path");const f=p.join(os.homedir(),".claude","metrics","costs.jsonl");console.log(fs.existsSync(f)?"cost log found":"cost log not found: "+f)' If the log is missing, do not fabricate usage data. Tell the user that cost tracking populates after the first session ends with the stop:cost-tracker hook enabled. Example — summary, by model, last 7 days node -e ' const fs=require("fs"),os=require("os"),path=require("path"); const f=path.join(os.homedir(),".claude","metrics","costs.jsonl"); if(!fs.existsSync(f)){console.log("cost log not found: "+f);process.exit(0);} const rows=fs.readFileSync(f,"utf8").split(/\r?\n/).filter(Boolean).map(l=>{try{return JSON.parse(l)}catch{return null}}).filter(Boolean); const bySession=new Map(); for(const r of rows){const k=r.session_id||r.transcript_path||r.timestamp;const p=bySession.get(k);if(!p||String(r.timestamp)>String(p.timestamp))bySession.set(k,r);} const latest=[...bySession.values()]; const cost=r=>Number(r.estimated_cost_usd)||0, day=r=>String(r.timestamp||"").slice(0,10), sum=a=>a.reduce((s,r)=>s+cost(r),0), f4=n=>"$"+n.toFixed(4); const today=new Date().toISOString().slice(0,10), yest=new Date(Date.now()-864e5).toISOString().slice(0,10); console.log("today: "+f4(sum(latest.filter(r=>day(r)===today)))+" | yesterday: "+f4(sum(latest.filter(r=>day(r)===yest)))+" | total: "+f4(sum(latest))+" ("+latest.length+" sessions)"); const m=new Map();for(const r of latest){const k=r.model||"(unknown)";m.set(k,(m.get(k)||0)+cost(r));} console.log("by model:");[...m.entries()].sort((a,b)=>b[1]-a[1]).forEach(([k,v])=>console.log(" "+f4(v)+" "+k)); ' For a session drilldown or CSV export, iterate the same latest set (or the raw rows for CSV) and print the fields you need. Reporting Guidance When presenting cost data, include today's spend vs yesterday, total across all sessions, a by-model breakdown, and session count. Format sub-dollar amounts with four decimals, larger amounts with two. Anti-Patterns Do not sum every row — they are cumulative per session; reduce to the latest row per session_id first. Do not estimate costs from raw token counts when estimated_cost_usd is present. Do not assume the log exists without checking. Do not hard-code current model pricing in user-facing answers. Do not recommend installing unreviewed hooks or plugins that execute arbitrary code. Related /cost-report - Command-form report over the same metrics log. cost-aware-llm-pipeline - Model-routing and budget-design patterns. token-budget-advisor - Context and token-budget planning. strategic-compact - Context compaction to reduce repeated token spend.
このスキルを起動するキーワード。クリックでコピーできます。

このスキルにはトリガーワードがありません。

ダウンロードした .skill に含まれるフィールド。
フィールド 説明
formatフォーマット識別子(skill/v1)
skill_idスキル固有 ID
nameスキル名
versionバージョン
description説明
categoryカテゴリ(配列)
trigger_wordsトリガーワード
tagsタグ
sourceソース
source_urlソース URL(本ページ)
exported_atエクスポート日時(ダウンロード毎)
system_promptシステムプロンプト本文
model_configモデル設定:provider / model / temperature / max_tokens / top_p
examplesサンプル
install_guide各プラットフォームの導入説明(Coze / Dify / Claude / カスタム)
同じスキルを各プラットフォーム形式で出力できます。
.skill 標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能 ダウンロード
.skillpro 拡張形式。scripts / tools / dependencies / hooks を含む ダウンロード
.json 純粋な JSON 出力。system_prompt とモデル設定のみ ダウンロード
Coze frontmatter 付き Markdown。Coze へのインポート用 ダウンロード
Dify Dify DSL。アプリ作成後にそのままインポート ダウンロード

每日精选 Skill 推荐,免费送到你邮箱

输入邮箱,每天接收一个精选 AI Agent 技能推荐。完全免费,持续更新。

验证码 --

提交后我们会发送一封确认邮件,点击邮件里的链接才会开始收信。

完全免费,取消任意时间。我们不会发送垃圾邮件。