Skip to main content

Usage and cost analytics for GitHub Copilot and Copilot-CLI session logs

Project description

copilot-session-usage

CI Coverage PyPI Python Versions Docs Code style: ruff Type checked License: MIT

Extract VS Code Copilot session cost KPIs (tokens, estimated USD, model, duration) from local debug logs.

Full documentation: copilot-session-usage.readthedocs.io

Installation

uv tool install copilot-session-usage

Quick start

# Analyze the most recent session
copilot-session-usage latest

# Analyze a specific session by its debug-log directory
copilot-session-usage analyze /path/to/session/debug-logs

# List recent sessions (metadata only)
copilot-session-usage list

# Batch analyze the last 10 sessions
copilot-session-usage batch 10

# Aggregate cost across all sessions matching a PRD path
copilot-session-usage analyze --name "PRD: /path/to/prd" --aggregate --format table

# List sessions in a debug-logs folder with cost columns
copilot-session-usage list --dir /path/to/debug-logs --format table

Features

  • Token-level cost estimation — per-model pricing with cache-hit discounts
  • Multi-model sessions — correctly handles sessions that call multiple models (e.g. Claude + Kimi)
  • Threshold-aware pricing — long-context tier switching (e.g. GPT-5.4 > 272k tokens)
  • Subagent cost attribution — tracks runSubagent calls and their token usage
  • Cross-platform — macOS, Linux, Windows, WSL2
  • Three output formatsjson (default), table, detailed
  • Three detail levelsminimal, compact, full
  • JSON and table output — machine-readable or human-friendly
  • Session filtering — regex match by name, date-range filtering
  • Aggregation — roll up costs across many sessions in one command
  • Skill-aware cost attribution — detect skills, attribute LLM and tool calls to the active skill
  • Skill cost breakdown — per-skill token counts and estimated cost
  • Tool-call attribution — per-skill/per-subagent tool-call counts
  • Title filtering — find sessions by title substring
  • Efficiency summaries — cache ratio, model split, cost per 1M tokens
  • Field extraction — pull specific values with --query

How it works

copilot-session-usage reads VS Code Copilot debug logs stored in ~/Library/Application Support/Code/User/workspaceStorage/ (macOS), %APPDATA%\Code\User\workspaceStorage\ (Windows), or ~/.config/Code/User/workspaceStorage/ (Linux).

Each session directory contains a GitHub.copilot-chat/debug-logs/ folder with JSONL files. The tool parses these files, extracts token counts per model, applies per-model pricing (including cache-hit discounts and long-context tier switching), and estimates the session cost in USD.

Subagent calls (runSubagent) are tracked separately so you can see how much token usage was delegated to helper agents.

Knowledge base

This project includes an OKF knowledge bundle in knowledge/ with structured guidelines for contributors. Validate it with:

just knowledge-validate

Usage

Commands

Command Description
analyze [PATH] Analyze one session by PATH, or many by --name regex
latest Analyze the most recently modified session
find TITLE Find and analyze a session by title (fuzzy match)
id SESSION_ID Analyze a session by exact UUID
list List recent sessions (metadata only by default)
batch N Analyze the N most recent sessions in one pass
skills List skills used across sessions with aggregated cost

Analysis options

Option Description
--name REGEX Filter sessions by title/ID regex (case-insensitive)
--title SUBSTRING Filter sessions by title substring (case-insensitive)
--since DATE Only sessions created after DATE (ISO 8601 with timezone)
--until DATE Only sessions created before DATE (ISO 8601 with timezone)
--workspace PATH Only sessions from this workspace folder
--aggregate Aggregate all matching sessions into one summary
--summary Output a cost-efficiency summary
--skill-breakdown Emit a per-skill cost breakdown
--tool-breakdown Emit a per-skill/per-subagent tool-call count breakdown
--skill NAME Filter the report to a single skill
--query PATH Extract a single field with dot notation
--query-help Print all --query field paths

Global options

Option Description
--workspace-storage PATH Override workspaceStorage directory (auto-detected by default)
--agent {vscode,cli} Provider to use (cli not yet implemented)
--detail {minimal,compact,full} Detail level (default: compact)
--format {json,table,detailed} Output format (default: table)
--output PATH Write output to file instead of stdout

Examples

# Full detail for the latest session
$ copilot-session-usage latest --detail full
{
  "session_id": "f5cbde8a-ec40-466f-86e6-f95c343b6c58",
  "session_dir": "/Users/az02065/Library/Application Support/Code/User/workspaceStorage/c016ff4fabbe9f918719a00c9c741058/GitHub.copilot-chat/debug-logs/f5cbde8a-ec40-466f-86e6-f95c343b6c58",
  ...
}

# JSON output for a specific session
$ copilot-session-usage analyze /path/to/debug-logs --format json --output report.json

# Find sessions containing "refactor" in the title
$ copilot-session-usage find "refactor"
Multiple sessions match 'implem':
  2026-07-01T21:15:12Z  'Implement copilot-session-usage spec'  (id: c890dd60-43d6-44f0-b57c-ab505dfa003b)
  2026-06-26T18:21:21Z  'Resume PRD implementation'  (id: 9368ab3e-1c93-4125-8271-d5bd024b057a)
  2026-06-26T09:19:52Z  'Resume Workflow PRD implementation'  (id: 1214eb3f-add0-41a5-84d4-88720218e60e)
...

# Get summary for a given session (found by `find`)
$ copilot-session-usage id 19e03be0-9cfa-4f21-a19a-4bdb754b3965 --format table
Session:   19e03be0-9cfa-4f21-a19a-4bdb754b3965
Title:     Implementation of new feature X
Started:   2026-07-01T20:37:34Z
Duration:  40588s  (active: 1083s)
Models:    claude-sonnet-4.6, claude-haiku-4.5, Kimi-K2.6-azure
Input:     1,425,790 tokens
Output:    22,166 tokens
Cached:    1,224,340 (86%)
LLM calls: 28
Est. cost: $1.0880
# Per-skill cost breakdown
$ copilot-session-usage id 19e03be0-9cfa-4f21-a19a-4bdb754b3965 --skill-breakdown --format table
Per-Skill Breakdown:
  Skill                              Input      Cached  Output  Calls     Cost
  ----------------------------------------------------------------------------
  /compendium-generic get-session-costs  1,137,864  1,015,825  15,729     24  $0.3636

# Per-skill/per-subagent tool-call counts
$ copilot-session-usage id 19e03be0-9cfa-4f21-a19a-4bdb754b3965 --tool-breakdown --format table
Tool Breakdown:
  Tool                          Calls  Skill                         Subagent
  ---------------------------------------------------------------------------
  read_file                        25  /compendium-generic get-session-costs  main
  vscode_askQuestions               3  /compendium-generic get-session-costs  main
  runSubagent                       1  /compendium-generic get-session-costs  main

# Concise skill cost (great for scripts)
$ copilot-session-usage id 19e03be0-9cfa-4f21-a19a-4bdb754b3965 \
    --skill "/compendium-generic get-session-costs" \
    --format json --detail minimal
{
  "skill": "/compendium-generic get-session-costs",
  "cost_usd": 0.3636,
  "input_tokens": 1137864,
  "output_tokens": 15729,
  "cached_tokens": 1015825,
  "llm_calls": 24
}

# List skills used across the last 7 days
$ copilot-session-usage skills --last 7d --format table
Skills across 23 sessions:
  Skill                              Sessions        Input     Output       Cached   Calls       Cost
  ---------------------------------------------------------------------------------------------------
  /compendium-generic get-session-costs       3    1137864      15729      1015825      24  $0.3636

# Filter sessions by title substring
$ copilot-session-usage list --title "get-session-costs"
$ copilot-session-usage analyze --title "grill-me" --latest
# Batch analyze last 5 sessions since July 1st
copilot-session-usage batch 5 --since 2026-07-01

# Aggregate all PRD-related sessions from the last week
copilot-session-usage analyze \
  --name "PRD: /path/to/prd" \
  --since 2026-06-30T00:00:00Z \
  --until 2026-07-07T00:00:00Z \
  --aggregate \
  --format table

# Cost-efficiency summary for a single session
copilot-session-usage analyze /path/to/debug-logs --summary --format table

# Extract just the total cost from a session
copilot-session-usage analyze /path/to/debug-logs --query .total.estimated_usd

# WSL2: point to Windows host workspaceStorage
copilot-session-usage latest \
  --workspace-storage /mnt/c/Users/$USER/AppData/Roaming/Code/User/workspaceStorage

Python API

from copilot_session_usage.api import (
    analyze_session,
    analyze_latest,
    batch_analyze,
    aggregate_sessions,
    list_sessions,
)

# Analyze a session by path
result = analyze_session(Path("/path/to/debug-logs"), detail="full")

# Analyze the most recent session
result = analyze_latest(detail="compact")

# Batch analyze the last 10 sessions
batch = batch_analyze(10, detail="minimal")

# Aggregate multiple full analyses into one efficiency summary
aggregate = aggregate_sessions([result1, result2])

# List sessions with regex and date-range filtering
sessions = list_sessions(
    name_pattern=r"PRD",
    since="2026-07-01T00:00:00Z",
    until="2026-07-07T00:00:00Z",
)

Development

# Install dependencies
just dev

# Run tests
just test

# Run full validation
just preflight

# Build docs
just docs

# Serve docs with auto-reload
just docs-serve

License

MIT — see LICENSE.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

copilot_session_usage-0.4.0.tar.gz (242.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

copilot_session_usage-0.4.0-py3-none-any.whl (38.1 kB view details)

Uploaded Python 3

File details

Details for the file copilot_session_usage-0.4.0.tar.gz.

File metadata

  • Download URL: copilot_session_usage-0.4.0.tar.gz
  • Upload date:
  • Size: 242.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for copilot_session_usage-0.4.0.tar.gz
Algorithm Hash digest
SHA256 b5efd96689fd4c008021a5080508fcf22ff2e9942b1008f607465a11f9425cbc
MD5 aa006c024a0bc877321cba5dffcb6be7
BLAKE2b-256 88c1011cc9f097dcf672d3aa11bd0ab49c551cd299d99823a8639ed6e801c5e0

See more details on using hashes here.

Provenance

The following attestation bundles were made for copilot_session_usage-0.4.0.tar.gz:

Publisher: publish.yml on gsemet/copilot-session-usage

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file copilot_session_usage-0.4.0-py3-none-any.whl.

File metadata

File hashes

Hashes for copilot_session_usage-0.4.0-py3-none-any.whl
Algorithm Hash digest
SHA256 42663f1c1d8da1372493e3efe0fdbd3088e1b7ebc72ec1c750c64d5080279dfd
MD5 2180319e92426efefce7867cc4ab0575
BLAKE2b-256 8810fb8f2481817155bc315610f5a805bef8eded6acc4a654fb18660445a9640

See more details on using hashes here.

Provenance

The following attestation bundles were made for copilot_session_usage-0.4.0-py3-none-any.whl:

Publisher: publish.yml on gsemet/copilot-session-usage

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page