Agent skill

Dora Metrics

by athola in athola/claude-night-market

Computes DORA delivery-performance metrics from git and GitHub API.

MITAuto-check passedDevelopment

Install Dora Metrics

skills CLI
$ npx skills add athola/claude-night-market --skill dora-metrics -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install athola/claude-night-market dora-metrics --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/athola/claude-night-market.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/minister/skills/dora-metrics .claude/skills/dora-metrics && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
dora-metrics
GitHub stars
341
Token cost
~1.2k tokens
SKILL.md length
456 words
Files
3
Skills in repo
152
Repo updated
First seen
Licence
MIT

At a glance

Computes DORA delivery-performance metrics from git and GitHub API.

  • Works in 5 steps: Run the helper script with the desired… → Read the output: per-metric value, tier… → For agentic-workflow audits, run the… → …
  • Assessing deployment frequency
  • SKILL.md covers Purpose, When To Use, When Not to Use and Workflow, plus 6 more sections
  • Calls python3 and cargo

What it does

Dora Metrics is an agent skill from athola/claude-night-market. Computes DORA delivery-performance metrics from git and GitHub API. Use when assessing deployment frequency, lead time, or change failure rate.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files (for example `modules/agentic-workflow-signals.md` and `modules/thresholds.md`).

It sits in Development, covering OKRs and executive reporting and Git workflow. It works with GitHub and Git. The repository describes itself as: 23 Claude Code plugins: TDD enforcement hooks, git/PR workflows, spec-driven development, code review, project lifecycle, fix-from-error, maintenance automation, context… The licence is MIT.

When your agent uses it

  • Assessing deployment frequency
  • Change failure rate

Example prompts

  • “Use the dora-metrics skill to compute DORA delivery-performance metrics from git and GitHub API”
  • “/dora-metrics”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Run the helper script with the desired window
  2. Read the output: per-metric value, tier classification, and the
  3. For agentic-workflow audits, run the same window twice. Once
  4. Optionally pipe --json into the tracker so trend data persists
  5. Optionally render trend charts with kuva when reviewing multiple

What it can do on your machine

Read from SKILL.md and the folder at commit 9f3eb00. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python3
    • cargo

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Dora Metrics loads about 1.2k tokens when it runs. Until then it costs about 39 tokens; SKILL.md has 456 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~39
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from athola/claude-night-market at commit 9f3eb00, republished under its MIT licence (© athola). 456 words, ~1,167 tokens.

Download SKILL.mdSave it as .claude/skills/dora-metrics/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
dora-metrics
description
Computes DORA delivery-performance metrics from git and GitHub API. Use when assessing deployment frequency, lead time, or change failure rate.
alwaysApply
false
category
governance
tags
dora, metrics, delivery, engineering-management, github
provides.governance
dora-tier, delivery-bottleneck
provides.reporting
dora-report, tier-classification
usage_patterns
delivery-retro, agentic-pipeline-audit, release-health-input
complexity
intermediate
model_hint
standard
estimated_tokens
800
progressive_loading
true

DORA Metrics

Purpose

Compute the four DORA delivery-performance metrics (Deployment Frequency, Lead Time for Changes, Change Failure Rate, and Time to Restore Service) from local git history and the GitHub API. Classify each metric into Elite, High, Medium, or Low using thresholds from DORA's State of DevOps research, and surface the single weakest dimension as the next improvement target.

When To Use

  • Engineering management retrospectives and quarterly reviews.
  • Auditing whether agentic workflows (AI-assisted PRs, automated deploys) improve velocity and stability or quietly regress them.
  • Feeding a tier signal into minister:release-health-gates.

When Not to Use

  • Single-team velocity tracking that needs story-point burndowns rather than delivery-performance evidence.
  • Repositories without a clear production branch or release cadence; DORA assumes one.

Workflow

  1. Run the helper script with the desired window:

    bash
    python3 -m minister.dora_metrics --window 30 --branch main
  2. Read the output: per-metric value, tier classification, and the bottleneck pointer.

  3. For agentic-workflow audits, run the same window twice. Once filtering to AI-authored PRs (e.g., --failure-label ai-bug), once across all PRs. Compare the CFR delta. See modules/agentic-workflow-signals.md.

  4. Optionally pipe --json into the tracker so trend data persists alongside release-health-gates snapshots.

  5. Optionally render trend charts with kuva when reviewing multiple windows or comparing before/after an agentic-workflow change:

    bash
    # Collect weekly snapshots into a TSV, then plot all four metrics
    # week<TAB>metric<TAB>value
    kuva line trends.tsv --x week --y value --color-by metric \
        --title "DORA trends (30-day windows)" -o dora-trends.svg
    
    # Quick terminal preview without writing a file
    kuva line trends.tsv --x week --y value --color-by metric --terminal

    kuva reads TSV/CSV from stdin or a file path. Install once: cargo install kuva --features cli. No project source changes required. See kuva for the full plot-type reference.

Inputs

FlagDefaultMeaning
--window30Measurement window in days
--branchHEADProduction branch
--failure-labelbugGitHub label marking prod failures
--jsonoffEmit JSON instead of human-readable
--repo-pathcwdRepository directory
Show full SKILL.md (199 more words)Show less

Outputs

A short text report or JSON payload with:

  • Per-metric numeric value (e.g., 4.2/day, 2.1 hours, 8%).
  • Per-metric tier (Elite, High, Medium, Low).
  • Overall tier (the weakest of the four).
  • Bottleneck key, identifying which metric to focus improvement on.

Tier Thresholds

See modules/thresholds.md for the complete table. Brief summary:

MetricEliteHighMediumLow
DF>= 1/day>= 1/week>= 1/month< 1/month
LT<= 1 day<= 1 week<= 1 month> 1 month
CFR<= 15%<= 30%<= 45%> 45%
TRS< 1 hour< 1 day< 1 week>= 1 week

Verification

Confirm a DORA report is real by re-running the script over a narrower window and checking that DF and LT scale predictably. For CFR and TRS, sample two or three of the contributing GitHub issues and verify the bug (or chosen) label is correct on each.

Testing

Unit tests live in plugins/minister/tests/unit/test_dora_metrics.py. Each tier boundary is exercised at the threshold, so future contributors who adjust an inequality (> vs >=) trigger a failure rather than a silent regression. Add new tests at the threshold when extending classification logic.

Exit Criteria

  • DORA report generated for the requested window.
  • All four metrics classified into a tier.
  • Bottleneck dimension surfaced.
  • Output is readable in a terminal or as a PR comment.

© athola, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files in plugins/minister/skills/dora-metrics of athola/claude-night-market.

  • SKILL.md
  • modules/agentic-workflow-signals.md
  • modules/thresholds.md

Open the folder on GitHubat commit 9f3eb00

Compare with similar skills

Dora Metrics next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Dora Metrics compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Dora Metrics this skillathola/claude-night-market341—~1.2kAutomated safety check: PassMIT
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Ansible Backport Creatoransible/ansible71k—~1.2kAutomated safety check: PassGPL-3.0
Worktrunk Release Workflowmax-sixty/worktrunk9.2k—~7.5kAutomated safety check: PassCustom licence
Git Gh Pat AuthNEventStore/NEventStore1.6k—~828Automated safety check: PassMIT
ZCF Release AutomationUfoMiao/zcf6.1k—~3.4kAutomated safety check: PassMIT

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Works with

Questions about Dora Metrics

What does Dora Metrics do?

Computes DORA delivery-performance metrics from git and GitHub API. Dora Metrics is an agent skill from athola/claude-night-market. Computes DORA delivery-performance metrics from git and GitHub API.

When should I use Dora Metrics?

Dora Metrics fits situations like: assessing deployment frequency; change failure rate.

How do I install Dora Metrics in Claude Code?

Run `npx skills add athola/claude-night-market --skill dora-metrics -a claude-code`. Or copy the skill folder (plugins/minister/skills/dora-metrics in athola/claude-night-market) into .claude/skills/dora-metrics in your project. Claude Code loads it when a task matches its description.

How do I install Dora Metrics in Codex?

Run `npx skills add athola/claude-night-market --skill dora-metrics -a codex`. Or copy the skill folder (plugins/minister/skills/dora-metrics in athola/claude-night-market) into .agents/skills/dora-metrics in your project. Codex loads it when a task matches its description.

Can I use Dora Metrics in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add athola/claude-night-market --skill dora-metrics -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/dora-metrics, .gemini/skills/dora-metrics, .github/skills/dora-metrics and .opencode/skills/dora-metrics in your project.

What does Dora Metrics need to run?

Going by SKILL.md and its folder, Dora Metrics needs the command-line tools its instructions call (python3 and cargo). Our summary lists: Python 3.

Does Dora Metrics access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Dora Metrics safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Dora Metrics use?

Dora Metrics is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Dora Metrics use?

About 1.2k tokens (SKILL.md is roughly 4.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Dora Metrics?

Skills that share tags, products or a category with Dora Metrics: Hunk Release Workflow (modem-dev/hunk, 9.6k stars), Ansible Backport Creator (ansible/ansible, 71k stars), Worktrunk Release Workflow (max-sixty/worktrunk, 9.2k stars) and Git Gh Pat Auth (NEventStore/NEventStore, 1.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Dora Metrics?

athola (a GitHub user) maintains it in athola/claude-night-market, which has 341 GitHub stars. The repository holds 152 skills in this directory. The repository was last updated on October 9, 2026.

Source: athola/claude-night-market on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.