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claude-usage

Report ground-truth Claude token consumption and estimated cost by parsing JSONL session files directly. Use when checking API spend, auditing token usage by project/session/model, generating daily/weekly/monthly cost reports, or diagnosing ccusage undercounting. Includes subagen

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Prix non confirmé★ 41 Stars GitHubRegistre mis à jour · 10 sept. 2026agent-skill

Vue d’ensemble

Report ground-truth Claude token consumption and estimated cost by parsing JSONL session files directly. Use when checking API spend, auditing token usage by project/session/model, generating daily/weekly/monthly cost reports, or diagnosing ccusage undercounting. Includes subagent files that ccusage ignores.

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Claude Usage

Ground-truth token usage and cost reporting for Claude Code sessions. Parses JSONL files directly—parent sessions and subagent sidechains—to produce accurate numbers.

Why This Exists

ccusage (v18+, the standard community tool with 10.6k stars) undercounts output tokens by 77-94% for heavy users:

SourceOutput TokensNotes
Raw JSONL (all files)1,076,691Ground truth
Raw JSONL (date-filtered)412,987Properly filtered
ccusage --timezone UTC93,96077% undercount
ccusage default62,37594% undercount

Three compounding bugs:

  1. Ignores subagent files at {session-uuid}/subagents/{agent-id}.jsonl—132 files missed on a typical day with Agent Teams
  2. Timezone confusion between UTC entry timestamps and local time filtering
  3. Drops entries in parent files—even at UTC, reports only 23% of actual tokens

This script reads every JSONL file to produce correct totals.


Usage

# Today's usage (default)
python3 ~/.claude/skills/claude-usage/scripts/claude_usage.py

# Last 7 days, broken down by day
python3 ~/.claude/skills/claude-usage/scripts/claude_usage.py --since 7d

# Weekly breakdown for the past month
python3 ~/.claude/skills/claude-usage/scripts/claude_usage.py --by week --since 30d

# Per-model breakdown
python3 ~/.claude/skills/claude-usage/scripts/claude_usage.py --by model --since 7d

# Per-session with human-readable summaries
python3 ~/.claude/skills/claude-usage/scripts/claude_usage.py --by session --since 1d

# Per-project breakdown
python3 ~/.claude/skills/claude-usage/scripts/claude_usage.py --by project --since 7d

# Filter to one project
python3 ~/.claude/skills/claude-usage/scripts/claude_usage.py --project Thera --since 30d

# Custom date range
python3 ~/.claude/skills/claude-usage/scripts/claude_usage.py --since 2026-02-01 --until 2026-02-28

# JSON output (pipe to jq)
python3 ~/.claude/skills/claude-usage/scripts/claude_usage.py --since 7d --json | jq '.grand_total'

# CSV output
python3 ~/.claude/skills/claude-usage/scripts/claude_usage.py --since 7d --csv

# Compare against ccusage (shows delta)
python3 ~/.claude/skills/claude-usage/scripts/claude_usage.py --compare

# PDF report (dark editorial, CTO-ready)
python3 ~/.claude/skills/claude-usage/scripts/claude_usage_report.py --since 30d

# PDF with custom output path
python3 ~/.claude/skills/claude-usage/scripts/claude_usage_report.py --since 30d -o ~/Desktop/feb-usage.pdf

# HTML only (no Playwright needed)
python3 ~/.claude/skills/claude-usage/scripts/claude_usage_report.py --since 7d --html

Output Columns

ColumnDescription
InputPrompt tokens (charged at input rate)
OutputResponse tokens (most expensive category)
CacheWCache write tokens (cache_creation_input_tokens)
CacheRCache read tokens (significantly cheaper than input)
TotalSum of all four token types
CostEstimated USD from the hardcoded pricing table

Aggregation Modes (--by)

ModeGroups byExample key
day (default)Calendar date in local timezone2026-02-20
weekISO week number2026-W08
monthMonth2026-02
sessionSession UUID (resolved to summary from sessions-index.json)8a6c801a Working on Claudicle...
modelModel nameclaude-opus-4-6
projectProject directory (decoded to path)~/Desktop/Programming

Pricing Table

Prices are hardcoded in the PRICING dict at the top of claude_usage.py. Update when Anthropic changes rates. Keys are model name substrings matched most-specific-first.

Current defaults (USD per million tokens, verified 2026-02-21):

ModelInputOutputCache Write (1h)Cache Read
Opus 4.5 / 4.6$5.00$25.00$10.00$0.50
Opus 4.0 / 4.1$15.00$75.00$30.00$1.50
Sonnet 4.x$3.00$15.00$6.00$0.30
Haiku 4.5$1.00$5.00$2.00$0.10
Sonnet 3.7 / 3.5$3.00$15.00$6.00$0.30
Haiku 3.5$0.80$4.00$1.60$0.08
Opus 3$15.00$75.00$30.00$1.50
Haiku 3$0.25$1.25$0.50$0.03

Cache write column shows the 1-hour rate (2x base input). Claude Code uses 1-hour prompt caching exclusively. The 5-minute rate (1.25x base input) is also supported when the JSONL cache_creation sub-object provides a TTL split.


Timezone Handling

JSONL timestamps are UTC. The script converts to the system's local timezone (or --tz America/New_York) before applying --since/--until filters. This prevents the midnight-boundary confusion that causes ccusage to drop entries when the UTC date differs from the local date.


Data Sources

JSONL files at ~/.claude/projects/{encoded-path}/:

  • Parent sessions: {session-uuid}.jsonl
  • Subagent sidechains: {session-uuid}/subagents/{agent-id}.jsonl
  • Session metadata: sessions-index.json (summaries for --by session)

The script uses streaming line-by-line reads (O(1) memory) to handle files exceeding 300MB.


PDF Reports

claude_usage_report.py generates a dark editorial PDF with Crimson Pro + JetBrains Mono typography, gold Minoan accents, bar charts, model distribution with color-coded stacked bars, token composition breakdown, and detailed tables. Designed for executive sharing.

Requires Playwright (uv pip install --system playwright && playwright install chromium). Uses Chromium for pixel-perfect CSS rendering—same engine as the Aldea Slide Deck skill. Falls back to HTML output with --html flag.


Caveats

  • Estimated accuracy: ~95%. The remaining gap comes from data residency multipliers (1.1x for US-only inference, not tracked) and potential edge cases in streaming chunk boundaries.
  • Streaming chunks are deduplicated by message ID using last-wins strategy—output_tokens monotonically increases across chunks, so only the final chunk per message ID has the correct value. Without dedup, costs were overcounted by 2-5x.
  • Cost is estimated from the pricing table. Anthropic billing may differ due to batch discounts or promotional pricing.
  • Cache write pricing uses the 1-hour rate by default (Claude Code's caching mode). When JSONL provides cache_creation.ephemeral_5m_input_tokens / ephemeral_1h_input_tokens, rates are split accordingly.
  • Synthetic entries (model: "<synthetic>") and billing error entries (all-zero token counts) are automatically filtered.
  • Malformed JSON lines and duplicate streaming chunks are counted and reported in the output footer.
  • Requires Python 3.9+ for zoneinfo module.
  • PDF reports require Playwright with Chromium (playwright install chromium). Includes a Pricing Methodology section with full rate table, formula, and confidence badge.
Métadonnées du fichier
name: claude-usage
description: Report ground-truth Claude token consumption and estimated cost by parsing JSONL session files directly. Use when checking API spend, auditing token usage by project/session/model, generating daily/weekly/monthly cost reports, or diagnosing ccusage undercounting. Includes subagent files that ccusage ignores.
Voir le texte original
---
name: claude-usage
description: Report ground-truth Claude token consumption and estimated cost by parsing JSONL session files directly. Use when checking API spend, auditing token usage by project/session/model, generating daily/weekly/monthly cost reports, or diagnosing ccusage undercounting. Includes subagent files that ccusage ignores.
---

# Claude Usage

Ground-truth token usage and cost reporting for Claude Code sessions. Parses JSONL files directly—parent sessions and subagent sidechains—to produce accurate numbers.

## Why This Exists

ccusage (v18+, the standard community tool with 10.6k stars) **undercounts output tokens by 77-94%** for heavy users:

| Source | Output Tokens | Notes |
|--------|-------------|-------|
| Raw JSONL (all files) | 1,076,691 | Ground truth |
| Raw JSONL (date-filtered) | 412,987 | Properly filtered |
| ccusage --timezone UTC | 93,960 | 77% undercount |
| ccusage default | 62,375 | 94% undercount |

Three compounding bugs:
1. **Ignores subagent files** at `{session-uuid}/subagents/{agent-id}.jsonl`—132 files missed on a typical day with Agent Teams
2. **Timezone confusion** between UTC entry timestamps and local time filtering
3. **Drops entries** in parent files—even at UTC, reports only 23% of actual tokens

This script reads every JSONL file to produce correct totals.

---

## Usage

```bash
# Today's usage (default)
python3 ~/.claude/skills/claude-usage/scripts/claude_usage.py

# Last 7 days, broken down by day
python3 ~/.claude/skills/claude-usage/scripts/claude_usage.py --since 7d

# Weekly breakdown for the past month
python3 ~/.claude/skills/claude-usage/scripts/claude_usage.py --by week --since 30d

# Per-model breakdown
python3 ~/.claude/skills/claude-usage/scripts/claude_usage.py --by model --since 7d

# Per-session with human-readable summaries
python3 ~/.claude/skills/claude-usage/scripts/claude_usage.py --by session --since 1d

# Per-project breakdown
python3 ~/.claude/skills/claude-usage/scripts/claude_usage.py --by project --since 7d

# Filter to one project
python3 ~/.claude/skills/claude-usage/scripts/claude_usage.py --project Thera --since 30d

# Custom date range
python3 ~/.claude/skills/claude-usage/scripts/claude_usage.py --since 2026-02-01 --until 2026-02-28

# JSON output (pipe to jq)
python3 ~/.claude/skills/claude-usage/scripts/claude_usage.py --since 7d --json | jq '.grand_total'

# CSV output
python3 ~/.claude/skills/claude-usage/scripts/claude_usage.py --since 7d --csv

# Compare against ccusage (shows delta)
python3 ~/.claude/skills/claude-usage/scripts/claude_usage.py --compare

# PDF report (dark editorial, CTO-ready)
python3 ~/.claude/skills/claude-usage/scripts/claude_usage_report.py --since 30d

# PDF with custom output path
python3 ~/.claude/skills/claude-usage/scripts/claude_usage_report.py --since 30d -o ~/Desktop/feb-usage.pdf

# HTML only (no Playwright needed)
python3 ~/.claude/skills/claude-usage/scripts/claude_usage_report.py --since 7d --html
```

---

## Output Columns

| Column | Description |
|--------|-------------|
| Input | Prompt tokens (charged at input rate) |
| Output | Response tokens (most expensive category) |
| CacheW | Cache write tokens (`cache_creation_input_tokens`) |
| CacheR | Cache read tokens (significantly cheaper than input) |
| Total | Sum of all four token types |
| Cost | Estimated USD from the hardcoded pricing table |

---

## Aggregation Modes (`--by`)

| Mode | Groups by | Example key |
|------|-----------|-------------|
| `day` (default) | Calendar date in local timezone | `2026-02-20` |
| `week` | ISO week number | `2026-W08` |
| `month` | Month | `2026-02` |
| `session` | Session UUID (resolved to summary from sessions-index.json) | `8a6c801a  Working on Claudicle...` |
| `model` | Model name | `claude-opus-4-6` |
| `project` | Project directory (decoded to path) | `~/Desktop/Programming` |

---

## Pricing Table

Prices are hardcoded in the `PRICING` dict at the top of `claude_usage.py`. Update when Anthropic changes rates. Keys are model name substrings matched most-specific-first.

Current defaults (USD per million tokens, verified 2026-02-21):

| Model | Input | Output | Cache Write (1h) | Cache Read |
|-------|-------|--------|-------------------|------------|
| Opus 4.5 / 4.6 | $5.00 | $25.00 | $10.00 | $0.50 |
| Opus 4.0 / 4.1 | $15.00 | $75.00 | $30.00 | $1.50 |
| Sonnet 4.x | $3.00 | $15.00 | $6.00 | $0.30 |
| Haiku 4.5 | $1.00 | $5.00 | $2.00 | $0.10 |
| Sonnet 3.7 / 3.5 | $3.00 | $15.00 | $6.00 | $0.30 |
| Haiku 3.5 | $0.80 | $4.00 | $1.60 | $0.08 |
| Opus 3 | $15.00 | $75.00 | $30.00 | $1.50 |
| Haiku 3 | $0.25 | $1.25 | $0.50 | $0.03 |

Cache write column shows the 1-hour rate (2x base input). Claude Code uses 1-hour prompt caching exclusively. The 5-minute rate (1.25x base input) is also supported when the JSONL `cache_creation` sub-object provides a TTL split.

---

## Timezone Handling

JSONL timestamps are UTC. The script converts to the system's local timezone (or `--tz America/New_York`) before applying `--since`/`--until` filters. This prevents the midnight-boundary confusion that causes ccusage to drop entries when the UTC date differs from the local date.

---

## Data Sources

JSONL files at `~/.claude/projects/{encoded-path}/`:
- **Parent sessions**: `{session-uuid}.jsonl`
- **Subagent sidechains**: `{session-uuid}/subagents/{agent-id}.jsonl`
- **Session metadata**: `sessions-index.json` (summaries for `--by session`)

The script uses streaming line-by-line reads (O(1) memory) to handle files exceeding 300MB.

---

## PDF Reports

`claude_usage_report.py` generates a dark editorial PDF with Crimson Pro + JetBrains Mono typography, gold Minoan accents, bar charts, model distribution with color-coded stacked bars, token composition breakdown, and detailed tables. Designed for executive sharing.

Requires Playwright (`uv pip install --system playwright && playwright install chromium`). Uses Chromium for pixel-perfect CSS rendering—same engine as the Aldea Slide Deck skill. Falls back to HTML output with `--html` flag.

---

## Caveats

- **Estimated accuracy: ~95%.** The remaining gap comes from data residency multipliers (1.1x for US-only inference, not tracked) and potential edge cases in streaming chunk boundaries.
- Streaming chunks are deduplicated by message ID using last-wins strategy—`output_tokens` monotonically increases across chunks, so only the final chunk per message ID has the correct value. Without dedup, costs were overcounted by 2-5x.
- Cost is estimated from the pricing table. Anthropic billing may differ due to batch discounts or promotional pricing.
- Cache write pricing uses the 1-hour rate by default (Claude Code's caching mode). When JSONL provides `cache_creation.ephemeral_5m_input_tokens` / `ephemeral_1h_input_tokens`, rates are split accordingly.
- Synthetic entries (`model: "<synthetic>"`) and billing error entries (all-zero token counts) are automatically filtered.
- Malformed JSON lines and duplicate streaming chunks are counted and reported in the output footer.
- Requires Python 3.9+ for `zoneinfo` module.
- PDF reports require Playwright with Chromium (`playwright install chromium`). Includes a Pricing Methodology section with full rate table, formula, and confidence badge.

Examiner la source

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Licence: MIT

  • Dependency or permission surface needs review
  • Permission surface may require sandboxing
  • SKILL.md lacks an explicit 'Limitations' section, though it mentions hardcoded pricing and timezone handling.
  • No installation/setup instructions are provided in SKILL.md; users must infer placement from the path in usage examples.
  • Low GitHub adoption signal
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • GitHub adoption: 41 GitHub stars
  • Stars/forks activity: 41 stars, 4 forks; issue activity unavailable in current metadata
  • Dependency/runtime risk: command execution surface, credential or environment access
  • Permission surface: secrets or environment access, shell or command execution
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Dépôt source
tdimino/claude-code-minoan
Licence
MIT
Version
1.0.0
Dernier push GitHub
6 sept. 2026
Registre mis à jour
10 sept. 2026

Version déclarée dans le registre ; vérifiez les versions de la source.

Qualité

60/100

Prometteur

Confiance

53/100

Do not auto-install

Audit

69/100

Revue nécessaire

  • Dependency or permission surface needs review
  • Permission surface may require sandboxing
  • SKILL.md lacks an explicit 'Limitations' section, though it mentions hardcoded pricing and timezone handling.
  • No installation/setup instructions are provided in SKILL.md; users must infer placement from the path in usage examples.
  • Low GitHub adoption signal
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • GitHub adoption: 41 GitHub stars
  • Stars/forks activity: 41 stars, 4 forks; issue activity unavailable in current metadata
  • Dependency/runtime risk: command execution surface, credential or environment access
  • Permission surface: secrets or environment access, shell or command execution
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      "SKILL.md lacks an explicit 'Limitations' section, though it mentions hardcoded pricing and timezone handling.",
      "No installation/setup instructions are provided in SKILL.md; users must infer placement from the path in usage examples.",
      "Low GitHub adoption signal",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "GitHub adoption: 41 GitHub stars"
    ]
  },
  "safety_gate": {
    "tier": "blocked",
    "label": "Blocked for auto-install",
    "auto_install_policy": "block",
    "auto_install_allowed": false,
    "human_review_required": true,
    "blocked": true,
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
  },
  "quality": {
    "score": 60,
    "label": "Promising"
  },
  "supply": {
    "track": "Coding and developer agents",
    "scenario": "Coding agents",
    "maintenance": "1mo since push",
    "risk": "Needs review"
  },
  "alternative_skills": [],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "production agents without a repository review",
    "Low GitHub adoption signal",
    "SKILL.md lacks an explicit 'Limitations' section, though it mentions hardcoded pricing and timezone handling.",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "No installation/setup instructions are provided in SKILL.md; users must infer placement from the path in usage examples."
  ],
  "agent_contract": {
    "task_input": "Use claude-usage in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 61/100 Manual review",
      "Audit: 69/100 Needs review",
      "Safety: 25/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "tdimino-claude-usage (claude-usage)",
      "install_command": "",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "tdimino-claude-usage",
      "task": "Use claude-usage in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/tdimino-claude-usage",
    "api": "https://www.openagentskill.com/api/agent/skills/tdimino-claude-usage",
    "audit": "https://www.openagentskill.com/skills/tdimino-claude-usage/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=tdimino-claude-usage&task=Use%20claude-usage%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20claude-usage%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20claude-usage%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/tdimino-claude-usage/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/tdimino-claude-usage"
  }
}

Pour le créateur

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Cette fiche a été indexée à partir de sources publiques et n’est pas marquée officielle tant qu’une revendication de mainteneur n’est pas approuvée.

Créateur
tdimino
Indexé par
Index communautaire OpenAgentSkill

L’attribution renvoie au dépôt public ou au profil du créateur. Les créateurs peuvent revendiquer la fiche pour mettre à jour les signaux de propriété.

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