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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 Curated skill Quality Excellent · 90 v1.0.0

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https://deepseekmodel.com/api/download.php?id=affaan-m-ecc-skills-cost-tracking-skill-md&format=skill
Download .skill Standard format with system_prompt and model_config, ready for any agent framework
The actual content of the system_prompt field in the .skill file.
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.
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The downloaded .skill package contains the following fields.
Field Description
formatFormat tag (skill/v1)
skill_idUnique skill ID
nameSkill name
versionVersion
descriptionDescription
categoryCategories (array)
trigger_wordsTrigger words
tagsTags
sourceSource
source_urlSource URL (this page)
exported_atExported at (set per download)
system_promptSystem prompt body
model_configModel config: provider / model / temperature / max_tokens / top_p
examplesExamples
install_guideImport guide for Coze / Dify / Claude / custom frameworks
The same skill can be exported in different platform formats.
.skill Standard format with system_prompt and model_config, ready for any agent framework Download
.skillpro Enhanced format with scripts, tools, dependencies and hooks Download
.json Plain JSON export with system_prompt and model parameters only Download
Coze Markdown with frontmatter, for Coze platform import Download
Dify Dify DSL, import directly after creating an app Download

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