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Ownership risk map

Skill ckorhonen/swe-skills/skills/ownership-risk-map

Claude Code skills for on-demand engineering work — PR risk review, repo introspection, audits, ownership maps. Published at cdd.dev/skills/swe.

Install
npx -y skills add ckorhonen/swe-skills --skill ownership-risk-map

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Maps engineering ownership risk in a repository using repo evidence such as git history, churn, bus factor, CODEOWNERS coverage, test density, and orphaned or unclear-owner surfaces. Use when a user says `map ownership risk`, `find bus factor hotspots`, `which files look orphaned`, `high-change low-test areas`, or asks for a recurring maintenance pass that identifies risky surfaces before they become incidents. Do NOT use for org charts, HR ownership assignments, or generic maintainer lists without repo evidence.

SKILL.md

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SWE Ownership Risk Map

What This Skill Does

Use this skill to identify where a repository is most exposed to ownership risk, not to build a people directory.

The goal is to produce a ranked map of surfaces that are likely to become fragile because of:

  • concentrated commit ownership
  • high churn with few distinct contributors
  • unclear or missing CODEOWNERS coverage
  • low test density near important code paths
  • stale or orphaned modules, scripts, or configs
  • recent turnover or repeated handoffs in the same surface

The output should be suitable for scheduled maintenance: short, repeatable, and easy to compare across runs.

When To Use

Use this skill when the user wants to:

  • find the highest-risk ownership hotspots in a repo
  • identify likely bus-factor problems before a change or release
  • run a recurring maintenance pass over high-churn or low-ownership areas
  • see which surfaces need better ownership, tests, or documentation

Do Not Use

Do not use this skill for:

  • assigning people to teams or building an org chart
  • generic repo orientation with no ownership-risk goal
  • general bug hunting or refactor planning
  • security audits that are not specifically about ownership risk

Inputs To Confirm

Confirm or infer:

  • repository or package scope
  • time window for the analysis, if any
  • whether the user wants the whole repo or a selected folder/package
  • whether CODEOWNERS or similar ownership metadata is available
  • whether the user wants a report-only pass or a ranked maintenance backlog

If the scope is missing, infer the current repository root and use a recent history window, but say so explicitly.

What To Optimize For

  • concrete repo evidence
  • honest unknowns when ownership is unclear
  • a short ranked list instead of a flat dump of names
  • actions that reduce ownership risk without broad rewrites
  • repeatable maintenance output that can be run on a schedule

Instructions

Step 1: Define The Scope

State the exact repo, package, folder, or service being reviewed.

If the user gives a time window, respect it exactly. If they do not, use the smallest recent-history window that still gives useful signal.

Step 2: Collect Ownership Evidence

Gather evidence from sources such as:

  • git history and commit authorship
  • churn over the chosen time window
  • CODEOWNERS or similar ownership files
  • test files and nearby validation coverage
  • CI or flaky-test signals tied to the surface
  • recent PRs or handoff clues in commit messages when available

Prefer direct evidence over inference. When you infer ownership risk from a pattern, label it as an inference.

Step 3: Identify Risk Surfaces

Look for surfaces such as:

  • files with a single dominant committer
  • high-change areas with only one or two contributors
  • code paths with weak tests or no nearby validation
  • configs, scripts, or glue code that seem maintained by no one
  • modules that have changed recently but lack clear ownership metadata
  • cross-cutting surfaces touched by many changes but few distinct owners

Rank each surface by the combination of:

  • bus factor
  • change frequency
  • test or validation coverage
  • ownership clarity
  • operational blast radius

Step 4: Separate Facts From Inference

For every risky surface, say:

  • what is directly observed
  • what is inferred
  • what remains unknown

Do not invent a maintainer just to make the map look complete.

Step 5: Propose Maintenance Actions

For the highest-risk surfaces, propose the smallest sensible follow-up actions such as:

  • add or update CODEOWNERS coverage
  • add a small validation test near the hotspot
  • document the ownership boundary in repo guidance
  • reduce hidden coupling with a narrow refactor
  • add a recurring review item for the surface

Keep the actions small and ownership-focused. Do not turn the map into a general cleanup backlog.

Step 6: Make It Recurring-Friendly

If the user implies a scheduled pass, include what should be compared across runs:

  • changed ranking
  • new or removed hotspots
  • surfaces that improved after prior follow-up
  • surfaces that remain orphaned or under-covered

Step 7: Keep The Output Evidence-Backed

If the repo does not have enough signal for a confident map, say so directly and list the missing evidence rather than guessing.

Output Requirements

Provide a report with these sections:

  1. Scope reviewed
  2. Evidence summary
  3. Ranked ownership-risk surfaces
  4. Recommended maintenance actions
  5. Unknowns or gaps

For each ranked surface, include:

  • area or files
  • observed evidence
  • inferred risk signal
  • why it matters
  • confidence level
  • smallest follow-up action

For any surface where evidence is weak, include:

  • what made the signal weak
  • what would strengthen it
  • explicit no-guess decision

Quality Bar

  • Rank by ownership risk, not by contributor count alone.
  • Keep the output short enough to compare between recurring runs.
  • Distinguish evidence from inference.
  • Prefer repository signals over people assumptions.
  • Be honest when ownership is unclear or missing.
  • Recommend only actions that directly reduce ownership risk.

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