agentsclimarketplace

Documents orchestrator

Skill Sheshiyer/skill-clusters/skills/documents-orchestrator

Hub-and-spoke agent-skill clusters, one per stack (Astro·GSAP·Remotion, Tauri, …). Installable via skills.sh.

Install
npx -y skills add Sheshiyer/skill-clusters --skill documents-orchestrator

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Route a document task to the right skill among the documents specialists — office formats (DOCX/PDF/PPTX/XLSX), docs sites, changelogs, OCR extraction, natural-language PDF edits, NotebookLM, and diagram authoring. USE WHEN a user wants to create, edit, extract from, convert, or publish a document but hasn't named the specific tool or format.

SKILL.md

4.1 KB, 888 tokens by cl100k_base, as published. Nobody here has run it

Documents Orchestrator

The single entry skill for document work. It locates the task on the format × intent map and delegates to one of 8 specialist spokes. The cross-cutting decision every document task shares — whether you need the editable source (round-trippable, structure preserved) or a rendered artifact (pixel-fidelity output you cannot edit back) — lives in documents-core; read it before you pick a tool, because the choice locks which spoke can touch the file next.

Cluster map (routing by intent → spoke + role)

Office documents (create / edit / extract / convert)

  • Word, PDF, PowerPoint, Excel — the full editable engine → documents (bundles docx/, pdf/, pptx/, xlsx/ subskills + a Playwright HTML→PDF report pipeline)
  • Quick natural-language PDF tweaks ("rotate page 3", "redact this") → nano-pdf

Extract & ingest (document → data)

  • Scanned/image PDF → text + structured data with confidence flags → deepread-ocr
  • Turn a corpus into a notebook, briefing, or podcast → notebooklm

Publish & narrate the docs themselves

  • Build/maintain a documentation site → mintlify
  • Generate user-facing release notes from git history → changelog-generator

Diagrams & visual documentation

  • Professional draw.io diagrams (flowcharts, BPMN, WBS/Gantt/RACI, network, UML) → drawio-diagrams-enhanced
  • Animate a Mermaid diagram into a GIF → mermaid-to-gif

Picked-up spokes

Additional documents spokes folded in from the antigravity-awesome-skills library (MIT). Route to these the same way — load on demand by reading their SKILL.md.

Author project docs

  • Write an absurdly thorough README.md after deep codebase exploration (tech stack, getting-started, architecture, env vars, scripts, testing, deployment, troubleshooting) → readme

Rendered marketing artifacts

  • Capture true-retina (2x) marketing screenshots of an app with Playwright — discover routes/features from the codebase, handle login, then shoot each view (Product Hunt / social / landing / docs) → screenshots (one-way render gate: produces PNGs you cannot edit back into the app)

Standard Operating Flow

  1. Classify the task: which format (DOCX/PDF/PPTX/XLSX/diagram/site) and which intent (create → edit → extract → convert → publish).
  2. Decide editable vs rendered (the model in documents-core). If the user needs to keep editing, stay in the native format and refuse a one-way render until they confirm.
  3. Delegate to the spoke(s). Multi-step asks fan out in pipeline order (e.g. "scan this contract and summarize" → deepread-ocr → notebooklm; "report from the assessment data" → documents ConsultingReport → Playwright PDF).
  4. Return: chosen spoke(s), whether output is editable or rendered, the format, and the next action.

Guardrails

See documents-core. In short: preserve the source — prefer the editable, round-trippable path; treat any render-to-PDF/OCR/GIF as a one-way gate and say so before crossing it. Never hardcode a value a formula should compute (XLSX), never silently flatten tracked changes (DOCX), and never trust OCR text without surfacing its confidence (deepread). Keep the original file intact; write derived artifacts alongside it, not over it.

Loading spokes on demand

To keep CLI startup context lean, this cluster's spokes are not separately registered as skills — only this orchestrator and its *-core are enumerated. When you route to a spoke named above, load it on demand by reading its file:

~/.agents/skill-clusters/skills/<spoke-name>/SKILL.md (or skills/<spoke-name>/SKILL.md inside the skill-clusters repo).

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.