metadata-only-wiki-sweep-workflow

Disciplined inventory process for cataloging documents by filename/path without content claims, using parent-centric grouping to prevent stub proliferation

5 stars

Best use case

metadata-only-wiki-sweep-workflow is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Disciplined inventory process for cataloging documents by filename/path without content claims, using parent-centric grouping to prevent stub proliferation

Teams using metadata-only-wiki-sweep-workflow should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/metadata-only-wiki-sweep-workflow/SKILL.md --create-dirs "https://raw.githubusercontent.com/vamseeachanta/workspace-hub/main/.agents/skills/workspace-hub/learned/metadata-only-wiki-sweep-workflow/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/metadata-only-wiki-sweep-workflow/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How metadata-only-wiki-sweep-workflow Compares

Feature / Agentmetadata-only-wiki-sweep-workflowStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Disciplined inventory process for cataloging documents by filename/path without content claims, using parent-centric grouping to prevent stub proliferation

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Metadata-Only Wiki Sweep Workflow

Use this when creating stub documentation for large document collections without making content claims. (1) Verify plan approval before execution. (2) Inventory all target directories and extract PDF metadata using `pdfinfo` for safe header-only reading when feasible. (3) Apply parent-centric grouping: merge fragment documents (page scans, figures, sections) into parent document entries rather than creating proliferating stubs. (4) Generate stubs with explicit "do not claim" sections listing what content verification hasn't occurred. (5) Validate stubs with regex checks for prohibited claim language ("normative", "shall", "must", "requires that") in actual content areas, excluding constraint headers.

## Large mixed-directory fallback (learned in Wave 4)

When the collection is very large or noisy (thousands of files with viewer binaries, image bundles, caches, or legacy app payloads), use a conservative fallback instead of forcing a long interactive agent run:

1. Prefer deterministic scripted generation (`execute_code` / Python) over prolonged interactive agent editing.
2. Keep writes inside the approved reporting surface only (for example `docs/reports/**`) if the issue does not require canonical registry/wiki updates.
3. Use conservative file-action classification:
   - `stub`: `.pdf`
   - `defer`: office/archive/text formats such as `.zip`, `.doc`, `.docx`, `.xls`, `.xlsx`, `.txt`, `.rtf`
   - `reject`: viewer binaries, caches, images, shortcuts, and app payloads such as `.dll`, `.fnt`, `.tif`, `.tiff`, `.db`, `.lnk`, `.gif`, `.png`, `.jpg`, `.jpeg`, `.exe`, `.ocx`, `.dat`, `.ini`, `.sys`
4. If PDF header extraction is too expensive for the volume, fall back to filename/path/extension-only metadata and state that explicitly in the artifact header.
5. For high-noise directories, surface the noise in the family map rather than trying to normalize everything into meaningful standards content.

## Interactive-agent recovery rule

If an interactive Codex run drifts into forbidden paths during a metadata-only sweep:
- stop it immediately,
- revert the forbidden path externally,
- narrow the agent back to report-only outputs,
- and if it still stalls, finish the artifact generation programmatically outside the agent session.

Treat the external git state as authoritative; do not trust the agent's verbal claim that cleanup is complete without verifying `git status`.

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