trusty-git-analytics

Analyze git repositories to measure developer productivity — classify commit work types, track weekly velocity, and export CSV/JSON/Markdown reports.

What It Does

tga walks one or more local git repositories, collects every commit into a SQLite database, classifies each commit into a work category (feature, bugfix, refactor, etc.) using a seven-tier classification cascade, then aggregates the results into per-author, per-week, DORA, velocity, and quality reports. It is a feature-complete Rust port of gitflow-analytics with the same YAML config schema and the same SQLite schema — existing config files work without modification.

Installation

From crates.io (recommended)

cargo install tga

This installs the tga binary to ~/.cargo/bin/. Ensure ~/.cargo/bin is in your PATH.

From source

git clone https://github.com/bobmatnyc/trusty-tools
cd trusty-tools/crates/trusty-git-analytics
cargo install --path .

Verify installation

tga --version
tga --help

Quick Start

Run Your First Analysis

Step 1 — Create a config.yaml:

repositories:
  - path: ~/code/my-project
    name: my-project

output:
  directory: ./reports
  formats: [csv, json, markdown]

Step 2 — Run the full pipeline:

tga analyze --config config.yaml

Step 3 — Find reports in ./reports/:

A full run writes 14 files: 9 CSV, 4 JSON, and 1 Markdown report. The most commonly used ones are:

reports/
├── authors.csv         # Per-author commit summary
├── weekly_activity.csv # Week-by-week breakdown
├── ... (7 more CSV files: DORA, velocity, quality, etc.)
├── report.json         # Full structured payload
├── ... (3 more JSON files)
└── report.md           # Narrative Markdown report

Configuration

Minimal config.yaml

repositories:
  - path: ~/code/my-repo
    name: my-repo

All other sections are optional. When output.formats is omitted, all three formats (CSV, JSON, Markdown) are written.

Full config reference

Key	Type	Default	Description
repositories	list	required	Repos to analyze
developer_aliases	map	{}	Canonical name → list of emails/aliases
team	object	—	Alternative to developer_aliases; roster with email
output.directory	path	./reports	Where reports are written
output.formats	list	[csv, json, markdown]	csv, json, and/or markdown
output.include_unclassified	bool	false	Include commits with no category
output.include_merges	bool	false	Include merge commits
output.include_files	bool	false	Include file-level change detail
classification.rules_file	path	—	Path to custom rules YAML/JSON
classification.use_llm	bool	false	Enable LLM fallback tier
classification.llm_model	string	gpt-4o-mini	LLM model identifier
classification.confidence_threshold	float	0.7	Minimum acceptance confidence
classification.llm_fallback_threshold	float	0.0	Commits with confidence above this value skip the LLM tier
classification.llm_fallback_concurrency	uint	8	Max concurrent LLM requests during fallback
github.token	string	$GITHUB_TOKEN	GitHub PAT for PR fetch
github.org	string	—	Org slug for org-wide PR queries
github.repo	string	—	Single repo slug (owner/name)
github.fetch_prs	bool	false	Fetch pull request metadata
github.ticket_regex	string	—	Override regex for detecting GitHub ticket refs in commit messages
jira.url	string	—	JIRA base URL
jira.username	string	—	JIRA API username (email for Cloud)
jira.token	string	—	JIRA API token
jira.project_key	string	—	Project key filter (e.g. API)
jira.ticket_regex	string	—	Override regex for detecting JIRA ticket refs in commit messages
linear.ticket_regex	string	—	Override regex for detecting Linear ticket refs in commit messages
pm.azure_devops.organization_url	string	—	ADO org URL (e.g. https://dev.azure.com/myorg)
pm.azure_devops.pat	string	—	Azure DevOps Personal Access Token
pm.azure_devops.project	string	—	Default ADO project name
pm.azure_devops.fetch_on_reference	bool	false	Fetch work items when AB#N refs appear in commits
pm.azure_devops.fetch_prs	bool	false	Fetch ADO pull requests and reviewer data
pm.azure_devops.ticket_regex	string	AB#(\d+)	Override regex for detecting ADO work item refs in commit messages
pm.bitbucket.workspace	string	—	Bitbucket Cloud workspace slug
pm.bitbucket.repo_slug	string	—	Repository slug within the workspace
pm.bitbucket.fetch_prs	bool	false	Fetch Bitbucket Cloud pull request metadata
pm.bitbucket.token	string	$BITBUCKET_TOKEN	Bearer token (App password or OAuth)
pm.bitbucket.username	string	—	Atlassian account username for Basic auth
pm.bitbucket.app_password	string	—	Atlassian App password for Basic auth (alternative to token)
cache.directory	path	—	Cache directory (supports ~)
version	string	—	Schema version; stored for compatibility
profile	string	—	Named profile; stored for compatibility

Paths support ~ expansion. Config files from the Python gitflow-analytics tool load without changes — unknown keys are silently ignored.

developer_aliases vs team.members

developer_aliases (Python-compatible flat map):

developer_aliases:
  "Alice Smith":
    - "alice@company.com"
    - "asmith@company.com"
    - "alice@personal.dev"
  "Bob Jones":
    - "bob@company.com"
    - "129991831+bobgithub@users.noreply.github.com"

team.members (structured roster with canonical email):

team:
  members:
    - name: Alice Smith
      email: alice@company.com
      aliases:
        - asmith@company.com
        - alice@personal.dev

When developer_aliases is non-empty it takes precedence over team.members. Use developer_aliases when migrating an existing Python config file; use team.members for new setups where canonical email matters for downstream tooling.

Example: multi-repo config with GitHub

See configs/example-config.yaml for a working example that covers multiple repositories, developer aliases, and CSV+Markdown output.

CLI Reference

All subcommands accept these global flags:

Flag	Default	Description
--config <PATH>	config.yaml	Path to config YAML
--database <PATH>	tga.db	Path to SQLite database
-v / -vv / -vvv	warnings only	Increase log verbosity

tga analyze

Run the full pipeline: collect → classify → report.

tga analyze [--config <PATH>] [--database <PATH>] [--output <DIR>]
            [--skip-collect] [--skip-classify] [--weeks <N>]
            [--from <DATE>] [--to <DATE>] [--dry-run]
            [--validate-only] [--no-validate]

Flag	Description
--skip-collect	Skip Stage 1; use commits already in the database
--skip-classify	Skip Stage 2; use existing classifications
--output <DIR>	Override output.directory from config
--weeks <N>	Limit collection to the last N weeks (overrides config start_date)
--from <DATE>	Start date for collection (ISO 8601 YYYY-MM-DD); mutually exclusive with --weeks
--to <DATE>	End date for collection (ISO 8601 YYYY-MM-DD); defaults to today
--dry-run	Perform all steps against an in-memory database; the on-disk database is left untouched
--validate-only	Run configuration validation and exit (0 on success, 1 on errors)
--no-validate	Skip pre-flight configuration validation

# Full pipeline
tga analyze --config config.yaml

# Re-run reports only (commits already collected and classified)
tga analyze --skip-collect --skip-classify --output ./reports-v2

tga collect

Stage 1: extract commits from git repositories into the database.

tga collect [--config <PATH>] [--database <PATH>]
            [--repos <NAME,...>] [--from <DATE>] [--to <DATE>] [--weeks <N>]
            [--since <DATE>] [--until <DATE>] [--dry-run]
            [--force-refresh-prs] [--validate-only] [--no-validate]

Flag	Description
--repos <NAME,...>	Comma-separated list of repository names to collect; others are skipped
--from <DATE>	Collect commits on or after this ISO 8601 date; mutually exclusive with --weeks
--to <DATE>	Collect commits on or before this ISO 8601 date; defaults to today
--since <DATE>	Legacy alias for --from (Python-predecessor compatibility); --from takes precedence
--until <DATE>	Legacy alias for --to (Python-predecessor compatibility); --to takes precedence
--weeks <N>	Limit collection to the last N weeks; --weeks takes precedence over --from/--to
--dry-run	Run collection against an in-memory database; the on-disk database is left untouched
--force-refresh-prs	Re-fetch ADO pull requests even when already cached (backfills pre-v1.0.9 rows)
--validate-only	Run configuration validation and exit (0 on success, 1 on errors)
--no-validate	Skip pre-flight configuration validation

tga collect --repos my-project --from 2024-01-01 --to 2024-03-31
tga collect --weeks 4   # collect last 4 weeks across all repos

tga classify

Stage 2: run the classification cascade over collected commits.

tga classify [--config <PATH>] [--database <PATH>]
             [--rules <PATH>] [--use-llm] [--backfill-complexity]

Flag	Description
--rules <PATH>	Override classification.rules_file from config
--use-llm	Enable LLM fallback regardless of config setting
--backfill-complexity	Fill missing complexity scores (1–5) for already-classified commits via the LLM, without re-running the full cascade; category, confidence, and method are left untouched

tga classify --rules ./custom-rules.yaml --use-llm

tga report

Stage 3: generate reports from classified commits.

tga report [--config <PATH>] [--database <PATH>]
           [--output <DIR>] [--formats <FMT,...>]

Flag	Description
--output <DIR>	Override output.directory from config
--formats <FMT,...>	Comma-separated: csv, json, markdown

tga report --output ./q1-reports --formats csv,json

tga pr-metrics

Aggregate pull-request metrics per engineer from the pull_requests cache.

tga pr-metrics [--config <PATH>] [--database <PATH>]
               [--weeks <N>] [--csv] [--output <PATH>]

Flag	Description
--weeks <N>	Limit metrics to PRs created within the last N weeks
--csv	Emit CSV instead of an aligned text table
--output <PATH>	Write output to a file (CSV with --csv, otherwise the text table)

tga pr-metrics --weeks 12 --csv --output pr-metrics.csv

The pr_comments_given and avg_revisions columns are reserved for future use and currently always output 0.0; the underlying review-comment and revision-count data is not yet tracked.

tga backfill

Retroactive maintenance operations that update existing commit rows in place (outside the normal collect → classify → report pipeline).

tga backfill <SUBCOMMAND> [--dry-run]

Subcommand	Description
ai-detection	Re-run LLM classification on low-confidence prior LLM verdicts
revert-flags	Scan commit messages for revert patterns and set is_revert
ticket-ids	Scan commit messages for ticket refs and update ticket_id/ticketed

Flag	Description
--dry-run	Report how many rows would change without writing

tga backfill revert-flags --dry-run
tga backfill ticket-ids

tga override

Manage manual classification overrides (Tier 0). Rows here pin a commit's verdict regardless of what the rule-based or LLM tiers would produce.

tga override <SUBCOMMAND>

Subcommand	Description
add <SHA> <WORK_TYPE> <CHANGE_TYPE> [--notes <TEXT>] [--repo <PATH>]	Insert (or replace) an override row for a commit SHA
list [--repo <PATH>]	List every override row, optionally filtered by repository
remove <SHA> [--yes]	Delete the override row(s) for a SHA (--yes skips confirmation)

tga override add abc1234 feature feature --notes "manual review"
tga override list
tga override remove abc1234 --yes

Pipeline Architecture

git repos ──┐
             │   collect      SQLite (tga.db)   classify       SQLite    report
GitHub API ──┼──────────────► [commits]        ──────────────► [classif]─────────► CSV (×9)
JIRA API ────┤   (libgit2,    [authors]         (7-tier                 ► JSON
Linear API ──┤   reqwest)     [pull_requests]   cascade,                ► Markdown
ADO API  ────┘                [work_items]      Rayon-parallel)

Stage 1 — collect (tga::collect): opens each repository with libgit2, walks the configured branch, extracts commit metadata and diff stats, resolves author identities, fetches GitHub PR / JIRA issue / Linear / Azure DevOps work item metadata via REST/GraphQL, and writes everything to SQLite.

Stage 2 — classify (tga::classify): reads unclassified commits from the database, runs each message through the seven-tier cascade (see below), and writes a classification verdict back. Rule-based tiers execute in parallel via Rayon.

Stage 3 — report (tga::report): reads the classified database, aggregates per-author, per-week, DORA, velocity, and quality statistics, and writes the configured output formats to the output directory.

Classification

Seven-Tier Cascade

Each commit message is tested against tiers in order. The first tier to produce a confident result wins.

Tier 0 — Manual Override (confidence 1.0): looks up the (commit_hash, repo_path) pair in the classification_overrides table. Managed via tga override add|list|remove.

Tier 1.5 — Issue Type (confidence 0.90): when the commit has ticket references resolving to rows in issue_cache, maps the upstream issue type (bug, story, task, spike, etc.) directly to a change_type.

Tier 3 — JIRA Project Mapping (confidence 0.95): when jira_project_mappings is configured, maps the JIRA project key prefix of any [A-Z]+-\d+ reference to a change_type.

Tier 4 — Exact (Aho-Corasick): builds a single finite-state machine from every keyword list across every rule and scans the message in O(n) time. Matches feat:, fix:, chore:, etc. Confidence 0.85–0.95.

Tier 5 — Regex: applies pre-compiled regex patterns from the rule set. Handles anchored conventional-commit patterns (^feat(\([^)]*\))?!?:) and JIRA ticket IDs (\b[A-Z][A-Z0-9]+-\d+\b).

Tier 6 — Fuzzy heuristics: detects merge commits (via is_merge flag or Merge pull request prefix) and reverts (via Revert prefix). No external dependencies.

Tier 7 — LLM fallback (optional, async): calls an OpenAI-compatible API (OpenRouter by default, AWS Bedrock behind the bedrock cargo feature) when tiers 0–6 leave a commit in a fallthrough category. Disabled by default; enable with analysis.llm_classification.enabled: true or --use-llm. Results are only accepted when confidence >= confidence_threshold (default 0.7).

Default Rules

ID	Category	Keywords / Patterns
cc-feat	feature	feat:, feature:, ^feat(...)?!?:
cc-fix	bugfix	fix:, bugfix:, hotfix, ^fix(...)?!?:
cc-chore	chore	chore:, ^chore(...)?!?:
cc-docs	documentation	docs:, doc:, ^docs?(...)?!?:
cc-refactor	refactor	refactor:, ^refactor(...)?!?:
cc-test	test	test:, tests:, ^tests?(...)?!?:
cc-ci	ci	ci:, ^ci(...)?!?:
cc-perf	performance	perf:, ^perf(...)?!?:
cc-style	style	style:, ^style(...)?!?:
cc-build	build	build:, ^build(...)?!?:
cc-revert	revert	revert:, ^revert(...)?!?:
breaking-change	breaking	breaking change, breaking-change
jira-ticket	feature (ticketed)	\b[A-Z][A-Z0-9]+-\d+\b
kw-bug	bugfix	bug, defect
kw-security	bugfix (security)	security, cve-, vulnerability

Commits that match no rule are assigned category uncategorized with confidence 0.0.

Custom Rules File

Supply your own rules alongside the defaults:

# my-rules.yaml
version: "1.0"
rules:
  - id: my-deploy
    category: deployment
    keywords:
      - "deploy:"
      - "release:"
    patterns:
      - "(?i)^deploy(ment)?:"
    priority: 80
    confidence: 0.9

tga classify --rules ./my-rules.yaml
# or in config.yaml:
# classification:
#   rules_file: ./my-rules.yaml

Output Formats

CSV

Nine CSV files are written when csv is in the format list (per-author, weekly activity, DORA metrics, velocity, quality, and related breakdowns). The two most commonly used are documented below.

authors.csv — one row per author:

Column	Description
name	Canonical author name
email	Canonical author email
commit_count	Total commits
insertions	Total lines added
deletions	Total lines deleted
files_changed	Total files changed
first_commit	ISO 8601 timestamp of earliest commit
last_commit	ISO 8601 timestamp of most recent commit

weekly_activity.csv — one row per week/author/repository bucket:

Column	Description
week	ISO week label, e.g. 2024-W03
author	Author name
repository	Repository name
commit_count	Commits in this bucket
insertions	Lines added in this bucket
deletions	Lines deleted in this bucket

JSON

Four JSON files are written when json is in the format list: report.json, velocity_summary.json, quality_summary.json, and dora_summary.json. The primary one is documented below.

report.json — full structured payload:

{
  "generated_at": "2024-03-15T10:00:00Z",
  "period_start": "2024-01-01T00:00:00Z",
  "period_end":   "2024-03-14T23:59:59Z",
  "total_commits": 347,
  "total_authors": 8,
  "category_breakdown": { "feature": 120, "bugfix": 45, ... },
  "authors": [
    {
      "name": "Alice Smith",
      "email": "alice@company.com",
      "commit_count": 87,
      "insertions": 4200,
      "deletions": 1100,
      "files_changed": 310,
      "categories": { "feature": 50, "bugfix": 20, ... },
      "first_commit": "...",
      "last_commit": "..."
    }
  ],
  "repositories": [
    {
      "name": "my-project",
      "commit_count": 347,
      "author_count": 8,
      "insertions": 18000,
      "deletions": 6000,
      "top_categories": [["feature", 120], ["bugfix", 45]]
    }
  ],
  "weekly_activity": [
    {
      "week": "2024-W03",
      "author": "Alice Smith",
      "repository": "my-project",
      "commit_count": 12,
      "insertions": 500,
      "deletions": 120,
      "categories": { "feature": 8, "bugfix": 4 }
    }
  ]
}

Markdown

report.md — a narrative report containing a summary header, per-author commit table, category breakdown, and weekly activity section. Suitable for pasting into Confluence or a PR description.

Development

Build and Test

# Build everything
cargo build

# Build release binary
cargo build --release

# Run all tests
cargo test

# Lint (zero warnings required)
cargo clippy -- -D warnings

# Format check (CI gate)
cargo fmt --check

# Auto-format
cargo fmt

# Generate rustdoc
cargo doc --open

Running Against Real Repos

configs/example-config.yaml is a working example that analyzes repositories using developer_aliases. Copy it, adjust paths and names to match your setup, then run:

tga analyze --config configs/example-config.yaml --database tga.db

CI Gates

The GitHub Actions workflow (ci.yml) requires:

• cargo fmt -- --check
• cargo clippy --all-targets -- -D warnings
• cargo test
• cargo doc --no-deps with RUSTDOCFLAGS="-D warnings"

Crate Structure

Single tga crate (consolidated from the original 5-crate workspace):

Module	Path	Purpose
tga::core	src/core/	Shared types, config, DB schema, migrations, error types
tga::collect	src/collect/	Stage 1: git extraction (libgit2), GitHub/JIRA/Linear/ADO clients, PmAdapter trait
tga::classify	src/classify/	Stage 2: seven-tier classification cascade
tga::report	src/report/	Stage 3: CSV/JSON/Markdown output
commands (binary-private)	src/commands/	Subcommand handlers wired into src/main.rs

License

Non-commercial use only. See LICENSE for terms.

Elastic License 2.0