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Evidence and privacy

Cleanr is AI-friendly by exposing deterministic local facts, not by embedding a model or letting a model delete files. The integration boundary is the read-only cleanr analyze command.

Local analysis contract​

Run analysis for one or more roots:

cleanr analyze /path/to/project

It also accepts --global and repeatable --global-kind <kind> options for known user-level cleanup locations. Its recommendation policy comes from the shared configuration:

[recommendations]
preselect_after_days = 90

Set preselect_after_days to 0 to disable the age gate, or to an integer from 1 through 3650. The TUI, cleanr analyze, cleanr plan, and cleanr dry-run use this same policy.

The command writes a versioned AnalysisReport JSON document to standard output. It only scans and evaluates evidence. It does not create a cleanup plan, change the current TUI selection, request cleanup authorization, or move files.

Install the agent skill​

The repository includes the cross-agent cleanr-review-disk-cleanup skill for this local, read-only workflow. Install that skill directly from GitHub with the open Skills CLI:

npx skills add drl990114/cleanr@cleanr-review-disk-cleanup -g

The installer detects supported local agents and lets you select the targets. The -g flag makes the skill available to your user account across projects; omit it to install only in the current project. You can also target an agent explicitly with -a <agent-name>.

Start a new task or session in the selected agent afterward. Invoke $cleanr-review-disk-cleanup where explicit skill invocation is supported, or ask the agent to review Cleanr disk-cleanup evidence. The skill is not tied to Codex: it uses the portable SKILL.md format and can be installed into any agent supported by Skills CLI. It only guides local read-only analysis; it has no cleanup authority and does not confirm, execute, or authorize cleanup.

What the report means​

One report has a fixed as_of time so age decisions are consistent at the threshold boundary. It includes:

  • schema and analysis identifiers, the policy snapshot, and completion time;
  • scan roots, integrity state, and structured scan issues;
  • each candidate's opaque report-scoped ID, local path, size, kind, and rollback method;
  • modification-time evidence, coverage, rule matches, and overlap resolution;
  • a deterministic recommendation state and decision codes explaining both a recommendation and a non-selection.

Modification time is observed filesystem metadata, not proof that a user last accessed a file. For a directory, Cleanr considers the newest observed modification time in its scanned descendants. Missing, future, partial, or incomplete evidence blocks automatic preselection.

  1. A local agent invokes cleanr analyze for a user-approved scope.
  2. It reads the report and proposes questions, explanations, or a review order.
  3. The user reviews candidates in Cleanr and makes the selection.
  4. Cleanr's local confirmation and execution checks authorize any cleanup.

The analysis command has no cleanup operation. An external agent's suggestion is never an execution token or permission.

Data boundary​

AnalysisReport is intentionally a local contract. It contains raw local paths, scan roots, rule reasons and risk notes, and issue paths. Cleanr has no embedded AI provider, API-key setting, prompt transport, or telemetry that sends this report elsewhere.

Do not forward the JSON to a remote service as-is. If you choose to share any of it, you are responsible for minimizing the scope and removing sensitive details. A safe remote-sharing feature would need a separate redacted DTO and an explicit threat-model review; the local report is not that DTO.