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Miro board

Workshop photos/notes -> an editable Miro diagram (real FRAMES as containers + stickies + connectors) with idempotent dedupe, rollback, undo and change commands, using the local script miro-push.mjs and env vars.

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High Signal

Workshop photos/notes -> an editable Miro diagram (real FRAMES as containers + stickies + connectors) with idempotent dedupe, rollback, undo and change commands, using the local script miro-push.mjs and env vars.

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Install for OpenClaw

Quick setup
  1. Download the package from Yavira.
  2. Extract the archive and review SKILL.md first.
  3. Import or place the package into your OpenClaw setup.

Requirements

Target platform
OpenClaw
Install method
Manual import
Extraction
Extract archive
Prerequisites
OpenClaw
Primary doc
SKILL.md

Package facts

Download mode
Yavira redirect
Package format
ZIP package
Source platform
Tencent SkillHub
What's included
miro-push.mjs, miro-ready.json, README.txt, SKILL.md, _out/.state.json

Validation

  • Use the Yavira download entry.
  • Review SKILL.md after the package is downloaded.
  • Confirm the extracted package contains the expected setup assets.

Install with your agent

Agent handoff

Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.

  1. Download the package from Yavira.
  2. Extract it into a folder your agent can access.
  3. Paste one of the prompts below and point your agent at the extracted folder.
New install

I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.

Upgrade existing

I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.

Trust & source

Release facts

Source
Tencent SkillHub
Verification
Indexed source record
Version
1.0.0

Documentation

ClawHub primary doc Primary doc: SKILL.md 16 sections Open source page

Goal

Produce a workshop output on Miro that is: readable as a diagram (not “scattered post-its”) easy to edit (real containers) idempotent (no duplicates) correctable (undo / delete / update)

Security (mandatory)

Never print MIRO_ACCESS_TOKEN Use only env vars: MIRO_ACCESS_TOKEN and MIRO_BOARD_ID Never use browser cookies/session tokens

Key rule: a container = a FRAME (not a shape)

A “workshop container” must be a FRAME when: there is a large rectangle/square with a clear title (e.g., “Easy vision”, “Milestone”, “VMS”, “Data Hub”, “Vico Insider”) or there is a swimlane/column with a title or a box is clearly grouping multiple elements (stickies or sub-boxes) Do NOT create a frame if: it’s just blank space without a title it’s only a decorative border without grouping meaning

HARD REQUIREMENT (do not violate)

You MUST create frames[] when the board contains categories/areas. You MUST assign a non-null frameId to each sticky (except explicit "outside notes"). If frames[] is empty OR if >10% stickies have frameId=null: DO NOT run the push command. Regenerate the structure (max 2 attempts).

Quality Gate — Container sanity check (mandatory)

If the image contains >=2 titled containers: frames.length MUST be >= 2 at least 95% of stickies MUST have a non-null frameId If not satisfied: DO NOT push Regenerate structure (max 2 attempts)

Mandatory planning (do not print)

Before generating JSON and before running DIRECT PUSH: Identify candidate FRAMES: any large rectangle with a title any area labeled on the side or centered above/below Assign every sticky to a candidate frame. If a sticky is ambiguous, add a warning and assign it to the closest/most plausible frame. Only after that, generate the final JSON.

Quality Gate (mandatory)

Before executing node ... apply: At least 1 frame must exist. At least 90% of stickies must have a non-null frameId. No frame should be “giant” if the image clearly contains multiple distinct areas. If the gate fails, DO NOT push: regenerate the structure (max 2 attempts).

Dedup / Idempotency (mandatory)

Every push must include a STABLE meta.sessionKey for the same diagram/topic (e.g., "easy-vision-workshop"). Every push must include a unique meta.runId (timestamp). If the sessionKey is the same: first remove the previous run (automatic undo) then apply the new one This prevents duplicates and repeated runs.

A) DIRECT PUSH (default if the user asks)

Generate a Miro-ready JSON (schema below) including: meta.sessionKey (stable) meta.runId (unique) Save the JSON to: ...\workshop-miro\_out\miro-ready-YYYYMMDD-HHMMSS.json Execute: node ...\miro-push.mjs apply <PATH_JSON> Reply with: frames created: N stickies created: N connectors created: N sessionKey + runId warnings (if any)

B) CORRECTIONS (when the user wants changes)

UNDO (per session): node ...\miro-push.mjs undo <sessionKey> If the user says “redo it better / wrong category / move things”: regenerate a corrected JSON with the same sessionKey run APPLY again (it replaces the previous run) Note: fine-grained edits (delete/update a single sticky) are a next step if the script supports them. Otherwise, recommended: full regeneration with the same sessionKey (cleaner and usually faster).

Smart layout rules

Inside each frame: left: inputs/sources center: processing / API / platforms right: outputs/UI/external integrations Spacing guideline: x += 420, y += 260 If there is a long arrow crossing the whole diagram: prefer 2 shorter connectors via an intermediate node (e.g., sticky “API” or “Integration”) if it improves readability

Connector / relationship rules

Create a connector when: you see an arrow/line on the whiteboard or the text implies a flow: "API", "sensoren", "data", "->", "integration" connector label: use the word that describes the flow (e.g., “API”, “Sensoren”, “Data”, “Milestone”) Default connector shape: "elbowed" (more readable for architecture diagrams).

Anti-overlap rules (clean arrows)

Goal: avoid connectors crossing over stickies/notes. Use default connector shape = "elbowed". Always keep a free “routing lane”: Do not place stickies close to frame borders. Minimum inner frame padding: 160px. If a connector would be long or would cross a cluster: create one or more “router nodes” (gray sticky with "." or empty text) placed outside clusters split the connection into segments: A -> R1 -> R2 -> B For connections between different frames: use a router node near the right border of the source frame and a router node near the left border of the target frame

JSON Output (FRAME-based)

{ "meta": { "title": "string", "source": "photo|notes", "language": "it|de|en", "createdAt": "ISO-8601", "sessionKey": "string (stable)", "runId": "string (unique)" }, "frames": [ { "id": "F1", "title": "string", "x": 0, "y": 0, "w": 1400, "h": 900 } ], "stickies": [ { "id": "S1", "frameId": "F1|null", "text": "string", "color": "light_yellow|light_blue|light_green|light_pink|gray", "x": 0, "y": 0, "unclear": false } ], "connectors": [ { "from": "S1", "to": "S2", "label": "string|null", "shape": "straight|elbowed|curved" } ], "warnings": [ "string" ] }

HARD Containment Detection (mandatory)

A "container" is a large rectangle that encloses other notes and has a title (e.g. "Product A", "Product B"). You MUST do this: Create one FRAME per container rectangle (title = the container title). Assign EVERY inner note to that frame via frameId. Only outer notes (explicitly outside all containers) may have frameId=null. Containment must be interpreted literally: If an element is visually inside the container boundaries, it belongs to that container. If unsure, assign to the nearest container and add a warning.

Quality checklist (before pushing)

sessionKey present and stable no giant “Workshop” frame unless the photo truly shows a single big box every sticky belongs to the correct frame (category) no duplicate stickies with identical text inside the same frame connectors only where they make sense (not between every pair)

Category context

Agent frameworks, memory systems, reasoning layers, and model-native orchestration.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package
2 Config1 Docs1 Scripts1 Files
  • SKILL.md Primary doc
  • miro-push.mjs Scripts
  • _out/.state.json Config
  • miro-ready.json Config
  • README.txt Files