Ouroboros PM Interview
Q00/ouroboros
Runs a guided product-manager interview that classifies each question automatically and produces a Product Requirements Document.
Turn a real network topology into a free, no-cost themed prompt preview, and optionally (after explicit confirmation) generate an explorable, AI-generated 3D 'world' via World Labs Marble — a…
$ npx skills add automateyournetwork/netclaw --skill worldlabs-topology-viz -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install automateyournetwork/netclaw worldlabs-topology-viz --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/automateyournetwork/netclaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/workspace/skills/worldlabs-topology-viz .claude/skills/worldlabs-topology-viz && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "worldlabs-topology-viz" agent skill from https://github.com/automateyournetwork/netclaw/tree/main/workspace/skills/worldlabs-topology-viz into .claude/skills/worldlabs-topology-viz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "worldlabs-topology-viz", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/automateyournetwork/netclaw/tree/main/workspace/skills/worldlabs-topology-vizType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add automateyournetwork/netclaw --skill worldlabs-topology-viz -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install automateyournetwork/netclaw worldlabs-topology-viz --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/automateyournetwork/netclaw.git skills-src && mkdir -p .agents/skills && cp -r skills-src/workspace/skills/worldlabs-topology-viz .agents/skills/worldlabs-topology-viz && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "worldlabs-topology-viz" agent skill from https://github.com/automateyournetwork/netclaw/tree/main/workspace/skills/worldlabs-topology-viz into .agents/skills/worldlabs-topology-viz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "worldlabs-topology-viz", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add automateyournetwork/netclaw --skill worldlabs-topology-viz -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install automateyournetwork/netclaw worldlabs-topology-viz --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/automateyournetwork/netclaw.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/workspace/skills/worldlabs-topology-viz .cursor/skills/worldlabs-topology-viz && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "worldlabs-topology-viz" agent skill from https://github.com/automateyournetwork/netclaw/tree/main/workspace/skills/worldlabs-topology-viz into .cursor/skills/worldlabs-topology-viz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "worldlabs-topology-viz", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/automateyournetwork/netclaw.git --path workspace/skills/worldlabs-topology-viz--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add automateyournetwork/netclaw --skill worldlabs-topology-viz -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install automateyournetwork/netclaw worldlabs-topology-viz --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/automateyournetwork/netclaw.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/workspace/skills/worldlabs-topology-viz .gemini/skills/worldlabs-topology-viz && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "worldlabs-topology-viz" agent skill from https://github.com/automateyournetwork/netclaw/tree/main/workspace/skills/worldlabs-topology-viz into .gemini/skills/worldlabs-topology-viz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "worldlabs-topology-viz", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install automateyournetwork/netclaw worldlabs-topology-vizInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add automateyournetwork/netclaw --skill worldlabs-topology-viz -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/automateyournetwork/netclaw.git skills-src && mkdir -p .github/skills && cp -r skills-src/workspace/skills/worldlabs-topology-viz .github/skills/worldlabs-topology-viz && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "worldlabs-topology-viz" agent skill from https://github.com/automateyournetwork/netclaw/tree/main/workspace/skills/worldlabs-topology-viz into .github/skills/worldlabs-topology-viz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "worldlabs-topology-viz", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add automateyournetwork/netclaw --skill worldlabs-topology-viz -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install automateyournetwork/netclaw worldlabs-topology-viz --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/automateyournetwork/netclaw.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/workspace/skills/worldlabs-topology-viz .opencode/skills/worldlabs-topology-viz && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "worldlabs-topology-viz" agent skill from https://github.com/automateyournetwork/netclaw/tree/main/workspace/skills/worldlabs-topology-viz into .opencode/skills/worldlabs-topology-viz/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "worldlabs-topology-viz", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
worldlabs-topology-vizTurn a real network topology into a free, no-cost themed prompt preview, and optionally (after explicit confirmation) generate an explorable, AI-generated 3D 'world' via World Labs Marble — a…
Worldlabs Topology Viz is an agent skill from automateyournetwork/netclaw. Turn a real network topology into a free, no-cost themed prompt preview, and optionally (after explicit confirmation) generate an explorable, AI-generated 3D 'world' via World Labs Marble — a decorative companion visualization, never a substitute for the accurate topology diagram it is derived from. Use when the operator asks for a fantastical, explorable, or AI-generated 3D world/scene of a network topology.
Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `fantastical_prompt_builder.py` and `topology_model.py`).
It sits in Product & Project Management. It works with Model Context Protocol. The repository describes itself as: An AI agent that claws through your network. The licence is Apache-2.0.
2 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit aa90e7d. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships script files (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
WLT_API_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Worldlabs Topology Viz loads about 2.9k tokens when it runs. Until then it costs about 109 tokens; SKILL.md has 1,321 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- **`WLT_API_KEY`** in `.env` — your World Labs API key (`platform.worldlabs.ai/api-keys`), with aAutomated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from automateyournetwork/netclaw at commit aa90e7d, republished under its Apache-2.0 licence (© automateyournetwork). 1,321 words, ~2,862 tokens.
.claude/skills/worldlabs-topology-viz/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.Version: 1.0.0 Feature: 122-worldlabs-topology-viz Status: Active
Produces an AI-augmented, explorable 3D "world" visualization of a real network topology, built on
top of the existing spec 121 topology-diagram-mcp pipeline. World Labs' Marble API is a generative
world model — it does not accept structured/graph input and has no mechanism for precise node
placement, so this is explicitly a decorative, companion visualization, never a replacement for
the accurate topology diagram. The real, structurally-correct diagram (produced by the existing,
unmodified topology-diagram-mcp/render_structural tool) remains the authoritative artifact and is
always referenced alongside any result this skill produces.
Two distinct modes:
worldlabs-marble-mcp tool itself (it will not proceed without user_confirmed=true).WLT_API_KEY in .env — your World Labs API key (platform.worldlabs.ai/api-keys), with a
funded account (platform.worldlabs.ai/billing). Required only for the generate mode — preview
needs no credential at all.worldlabs-marble-mcp server (mcp-servers/worldlabs-marble-mcp/), registered in
config/openclaw.json.topology-diagram-mcp server (spec 121), already registered — reused unmodified.Any topology snapshot already normalized into the devices/links shape topology-diagram-mcp
accepts (CML, pyATS, or any of NetClaw's other topology-of-record integrations, or a freeform
description).
Zero cost, instant, repeatable with a different theme. No call to worldlabs-marble-mcp is ever
made in this workflow.
topology-diagram-mcp/render_structural
already accepts: devices: [{"hostname","role","state"}], links: [{"a","b","label"}].topology-diagram-mcp/render_structural(snapshot_id, devices, links) — reused unmodified.
This tool has two existing failure modes that MUST both be surfaced clearly, distinctly, and
before anything else in this workflow runs (FR-012 and its Edge Cases correction):devices is empty): the tool raises "devices list is empty — nothing to render". Report exactly that — this topology has nothing to preview. Do not attempt to
fabricate a prompt or a result.render_structural already supports
it (a one-node layout), and this workflow proceeds normally.topology_model.TopologySnapshot from the same devices/links data (via
topology_model.Device/Link), and call
fantastical_prompt_builder.build_prompt(snapshot, theme=<operator-specified theme, or None for the default>).render_structural's image_base64, or a note of where it's shown).topology_model.DECORATIVE_LABEL, verbatim, every single time (FR-009) — this is a preview
of what could be generated, not a claim about what a generated world will precisely look
like (Marble is non-deterministic).This is the one part of this skill that spends real money. Only run this after Workflow: Free Preview has already produced a reference diagram and prompt for the same topology snapshot.
worldlabs-marble-mcp/generate_world(text_prompt=<from the preview's composed prompt>, display_name=<derived from the snapshot's identity, max 64 chars>, user_confirmed=true).
Do NOT pass image_base64 (research.md R9/R10, corrected 2026-09-03 after live evidence
from six real production generations): attaching the reference diagram as an image gets pasted
flat and unchanged into the generated scene instead of being used as structural guidance, and
is also measurably less reliable (3 of 4 image-bearing attempts failed; 4 of 4 text-only
attempts succeeded on the first try). fantastical_prompt_builder.build_prompt already
describes every real device and every real link individually in the text — that is the thing
that actually carries real data into the result, not the image. The user_confirmed=true
argument is the second, code-level layer (FR-016) — generate_world itself refuses to make any
outbound call without it, so this is not optional plumbing to skip.confirmation_required rejection —
which should never happen if step 1 was actually followed, but is handled the same way if it
does), record a GAIT entry via gait_record_turn (Constitution Principle IV, FR-015): user_text
names the topology snapshot's identity/theme and that the operator confirmed; assistant_text
names the operation_id and, once known, the world_id/world_marble_url/cost.total_credits
or the failure category; artifacts is empty or references the reference diagram's identity
only — never the API key, never raw device data beyond hostname/role identity. This step is
required for every confirmed attempt, not optional, and is distinct from any end-of-session GAIT
summary.operation_id (tell the operator to note it — nothing server-side tracks
it, Clarifications Q1), and that status can be checked later.confirmation_required: this means step 1/2 were skipped — report it and restart from
step 1, do not retry the call with the flag silently added.authentication_failure: tell the operator to check WLT_API_KEY — never repeat the key
value itself.insufficient_credits: pass through World Labs' own message (it already names the fix —
add credits or enable auto-refill).rate_limited: tell the operator to wait and retry later — do not resubmit automatically.generic_failure: pass through the provider's message.worldlabs-marble-mcp/check_generation_status(operation_id).done: false — still in progress; report that plainly.done: true with a response — completed. Report world_marble_url (the viewer link),
assets, and cost.total_credits, plus topology_model.DECORATIVE_LABEL verbatim, every
time (FR-009) — a completed generation is exactly the case someone could mistake for an
accurate diagram, so this label matters most here.done: true with an error — the generation itself failed after starting; report the error
plainly, and do not retry automatically.not_found_or_expired — the operation record itself expired (they carry a roughly one-hour
expires_at). If an earlier poll's metadata included a world_id, fall back to
worldlabs-marble-mcp/get_world(world_id) instead of reporting a hard failure — the world
itself is not necessarily gone just because the operation record is. Include
DECORATIVE_LABEL here too if get_world succeeds.For when the operator has already written a complete, ready-to-use prompt themselves (e.g.
iterating creatively on wording) and wants it sent straight to Marble — no topology fetch, no
render_structural call, no fantastical_prompt_builder, no other skill or data source
involved at all. The operator's own words are the entire text_prompt, verbatim.
worldlabs-marble-mcp/generate_world(text_prompt=<the operator's prompt, verbatim>, display_name=<a short label the operator gives, or a reasonable default>, user_confirmed=true)
— no image_base64, same reasoning as above.DECORATIVE_LABEL still applies:
a hand-written prompt with no topology data behind it at all is not a diagram substitute either."Give me a fantastical world preview of the CML lab topology, floating-islands theme"
"Preview what this topology would look like as an underwater city, using the current pyATS testbed"
"Show me a fantastical preview of this topology: a router r1 connected to a switch sw1""Yes, generate it"
"Go ahead and generate that world""<a full hand-written scene description>" send this straight to Marble and send me the link
"<a full hand-written scene description>" generate that, no need to pull any topology for this one"Is the world done yet?"
"Check the status of that generation"Unlike threejs-network-viz, blender-3d-viz, ue5-network-viz (precise, data-driven 3D scenes)
and comfyui-topology-viz (a stylized flat still image), this skill's output is a generative,
non-deterministic 3D world whose geometry is not driven by the topology's actual structure — only
its theme is. It is closer in spirit to concept art than to a diagram. Every result this skill
produces says so explicitly and points back to the accurate diagram it was generated from (FR-009).
© automateyournetwork, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 2 other files in workspace/skills/worldlabs-topology-viz of automateyournetwork/netclaw.
Open the folder on GitHubat commit aa90e7d
Worldlabs Topology Viz next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Worldlabs Topology Viz this skillautomateyournetwork/netclaw | 676 | — | ~2.9k | Automated safety check: Notes | Apache-2.0 | |
| Ouroboros PM InterviewQ00/ouroboros | 6.2k | — | ~5.7k | Automated safety check: Pass | MIT | |
| Jira Natural Language Interfacejjmartres/opencode | 133 | 3 repos | ~1.7k | Automated safety check: Pass | MIT | |
| Load Contextvishalmdi/ai-native-pm-os | 108 | — | ~562 | Automated safety check: Pass | None | |
| User Testing ValidatorIntelligent-Internet/zenith | 338 | — | ~1.8k | Automated safety check: Pass | Apache-2.0 | |
| ComposerFrkAk/piyaz | 194 | — | ~8.6k | Automated safety check: Warn | AGPL-3.0 |
Q00/ouroboros
Runs a guided product-manager interview that classifies each question automatically and produces a Product Requirements Document.
jjmartres/opencode
Lets an agent view, create, update and transition Jira issues in natural language, automatically choosing between the jira CLI and Atlassian MCP tools.
vishalmdi/ai-native-pm-os
Loads all PM context files and prepares Claude for a productive session.
Intelligent-Internet/zenith
Real-surface validation coordinator for engineering validation assignments.
FrkAk/piyaz
A skill your agent uses when the user types /piyaz:composer, /piyaz:composer <taskRef, or /piyaz:composer rework <taskRef|pr-url, or asks to run the next Piyaz task end-to-end, ship the backlog…
codingagentsystem/cas
Quick startup checklist for factory supervisors. An agent skill from codingagentsystem/cas.
automateyournetwork/netclaw
Entry point for designing EVE-NG network labs: classifies the request, gathers missing requirements, proposes options and validates the resulting topology.
automateyournetwork/netclaw
Deploys Cisco ACI policy changes only behind an approved ServiceNow Change Request, capturing pre and post-change fault baselines and rolling back automatically on a fault delta.
automateyournetwork/netclaw
Runs a phased health audit of a Cisco ACI fabric through MCP tools: node status, links, tenant and policy review, faults and endpoint learning.
automateyournetwork/netclaw
Validate Arista EOS network state against ANTA's pre-built 208-test catalogue, with structured pass/fail verdicts.
automateyournetwork/netclaw
Arista CloudVision Portal (CVP) automation via REST API — device inventory, events, connectivity monitoring, tag management (4 tools).
automateyournetwork/netclaw
AWS CloudWatch monitoring — metrics, alarms, log queries, VPC flow log analysis, network performance.
Works with
Turn a real network topology into a free, no-cost themed prompt preview, and optionally (after explicit confirmation) generate an explorable, AI-generated 3D 'world' via World Labs Marble — a…. Worldlabs Topology Viz is an agent skill from automateyournetwork/netclaw. Turn a real network topology into a free, no-cost themed prompt preview, and optionally (after explicit confirmation) generate an explorable, AI-generated 3D 'world' via World Labs Marble — a decorative companion visualization, never a substitute for the accurate topology diagram it is derived from.
Worldlabs Topology Viz fits situations like: the operator asks for a fantastical; AI-generated 3D world/scene of a network topology.
Run `npx skills add automateyournetwork/netclaw --skill worldlabs-topology-viz -a claude-code`. Or copy the skill folder (workspace/skills/worldlabs-topology-viz in automateyournetwork/netclaw) into .claude/skills/worldlabs-topology-viz in your project. Claude Code loads it when a task matches its description.
Run `npx skills add automateyournetwork/netclaw --skill worldlabs-topology-viz -a codex`. Or copy the skill folder (workspace/skills/worldlabs-topology-viz in automateyournetwork/netclaw) into .agents/skills/worldlabs-topology-viz in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add automateyournetwork/netclaw --skill worldlabs-topology-viz -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/worldlabs-topology-viz, .gemini/skills/worldlabs-topology-viz, .github/skills/worldlabs-topology-viz and .opencode/skills/worldlabs-topology-viz in your project.
Going by SKILL.md and its folder, Worldlabs Topology Viz needs Python for the scripts in its folder and credentials named WLT_API_KEY. Our summary lists: Python 3; A credential in WLT_API_KEY.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
Worldlabs Topology Viz is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.9k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Worldlabs Topology Viz: Ouroboros PM Interview (Q00/ouroboros, 6.2k stars), Jira Natural Language Interface (jjmartres/opencode, 133 stars), Load Context (vishalmdi/ai-native-pm-os, 108 stars) and User Testing Validator (Intelligent-Internet/zenith, 338 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
automateyournetwork (a GitHub user) maintains it in automateyournetwork/netclaw, which has 676 GitHub stars. The repository holds 120 skills in this directory. The repository was last updated on October 9, 2026.
Source: automateyournetwork/netclaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.