Provide implementations of advanced data structures
日本語の概要は準備中です。原文の説明を表示しています。
Atlas turns your STATED NEED into a real systems atlas by SCANNING your actual sources (Azure via `az`, git repos, local dirs) and process/data mining them, THEN enriching against the Atlas knowledge graph. Use this skill when asked to inventory/map your real systems, scan your cloud + repos + directories, mine the real processes or data they contain, or collect their real constraints/gotchas. (atlas, scan my systems, inventory our azure account, map my repos, real systems atlas, process mining, data mining, collect nuances, system discovery)
インストールする前に、エージェントに与えられる指示の中身を確認できます。
This skill turns a stated need into a real systems atlas by SCANNING your
actual sources — Azure subscriptions (via read-only az), git repos, and local
directories — and process/data mining them, THEN enriching the result against the
Atlas knowledge graph. It is the brain of the atlas plugin. The scan is
PRIMARY; the graph is SECONDARY. For non-trivial runs it delegates orchestration
to babysitter:babysit using an atlas-specific .a5c process; for simple
lookups it queries the graph directly.
The output you want is an evidence-backed inventory of your systems — e.g.
azure-inventory.json (every real resource id + RG from az),
workspace-inventory.json (real repo/dir scan), processes.json (real mined
CI/CD/IaC/.a5c processes), and a cross-linked SYSTEMS-ATLAS.md. Every item must
cite its REAL source. Generic catalog nodes are NOT the deliverable.
Bash to run READ-ONLY scans:
az (account/group/resource list + per-service list/show) for Azure;
git + filesystem (Read/Glob) for repos and directories. NEVER invent
resource ids, regions, SKUs, or file paths — if you didn't observe it in real
output, it does not go in the atlas. Only scan the sources named in the need
(scoping, not a fallback).mcp__atlas__atlas_public_* MCP tools (server URL overridable via
ATLAS_MCP_URL). Use it ONLY to add best-practice / comparison context for the
real systems you found — never as the primary content, never to pad the atlas
with generic nodes. See the atlas-graph-query skill for the tool surface.| Trigger phrase | Command |
|---|---|
| scan/inventory my real systems (azure + repos + dirs), map them | /atlas:discover |
| mine the real processes in my repos/cloud (CI/CD, IaC, .a5c, cron) | /atlas:mine-processes |
| mine the real data stores/models in my cloud + repos | /atlas:mine-data |
| collect the real constraints/gotchas of my scanned systems | /atlas:collect-nuances |
AskUserQuestion). Per repo policy, interview ONLY when truly unclear.az and write
a real cloud inventory citing resource ids/RGs. Skip cleanly (record a reason)
if no cloud source is in scope — only scan what's named.SYSTEMS-ATLAS.md, plus a machine mirror.For any non-trivial run, hand off to babysitter:babysit (via the Skill tool)
naming the matching atlas process:
/atlas:discover → atlas-systems-discovery/atlas:mine-processes → atlas-process-mining/atlas:mine-data → atlas-data-mining/atlas:collect-nuances → atlas-collect-nuancesDo not hand-roll orchestration when a process exists.
az
resource id / RG, or a file path). Never invent resource ids, regions, SKUs, or
file paths. Never invent graph node ids either — only reference ids returned by
the Atlas tools, and keep graph content strictly secondary.az read verbs, git status/remote/log, filesystem
reads. Never run mutating cloud/git/fs commands and never read secret values.Bash tool inside the agent
task prompt. Do not emit kind: 'shell' subtasks unless the user explicitly
asks for a shell-oriented workflow.まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Provide implementations of advanced data structures
日本語の概要は準備中です。原文の説明を表示しています。
Fresh adversarial code review with binary PASS/FAIL verdicts, evidence citations, and anchoring bias prevention via fresh reviewer spawning.
日本語の概要は準備中です。原文の説明を表示しています。
WASM-based instant code transforms for simple tasks, achieving 352x speedup over LLM inference with zero cost.
日本語の概要は準備中です。原文の説明を表示しています。
Coordinate Crew (persistent) and Polecat (transient) agents using Gas Town's hook-based work distribution and GUPP principle.
日本語の概要は準備中です。原文の説明を表示しています。
Generate visual representations of algorithm execution
日本語の概要は準備中です。原文の説明を表示しています。
Hierarchical coordination and drift detection with frequent checkpoints, shared memory coherence validation, role specialization enforcement, and short task cycles.
日本語の概要は準備中です。原文の説明を表示しています。