跳到正文
cccskills
免费在 GitHub 公开

ito-compute

Check live H100 or H200 GPU availability, request fixed-rate quotes, and review procurement status through the canonical Itô client. It also supports device credential revocation and explicitly authorized node checks; quote requests do not reserve capacity.

中文简介正在准备中。当前显示英语简介。

原文查看原文说明

Query live GPU inventory, submit an authenticated Itô fixed-rate RFQ, inspect RFQ or procurement status, revoke device credentials, and run explicitly gated node qualification through the separately installed canonical CLI. Use when a user asks to find H100/H200 capacity, request a fixed compute rate, check Itô compute status, validate GPU nodes, revoke Itô access, or rent or purchase GPU compute and needs the supported boundary explained.

查看安装方法

适用场景

  • Checking H100 or H200 availability
  • Requesting a fixed-rate compute quote
  • Reviewing quote and procurement status
  • Checking explicitly authorized GPU nodes
  • Revoking device access

包含的文件(2)

  • SKILL.md6.5 KB
  • agents/openai.yaml253 B

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Itô Compute

Use the canonical Itô compute CLI or MCP server. ECC does not implement a parallel client, local simulation, reservation, workload runner, or inference server. ECC itself does no browser automation.

Install the canonical local package

ito-compute-cli is currently unpublished. Build it from its canonical repository instead of using npx, npm exec, or an unverified package:

git clone https://github.com/Ito-Markets/ito-cloud-runtime.git
cd ito-cloud-runtime/cli/ito-compute-cli
npm ci
npm run check

Set ECC_ITO_CLI_EXECUTABLE to the explicit absolute built entry:

/absolute/path/to/ito-cloud-runtime/cli/ito-compute-cli/dist/bin/ito.js

ECC never discovers this credential-bearing client through PATH. ecc ito login performs device authorization and never inherits ITO_API_KEY. The validation-only auth, plus find and status, forward ITO_API_KEY directly when configured; ITO_AUTH_MODE=legacy is not required. Never put a key or token in arguments, tracked files, MCP results, logs, or chat.

CLI workflow

  1. Run ecc ito login before the first operation. ECC delegates this to the canonical CLI's device authorization, which opens the Itô verification page by default and persists a device token in macOS Keychain. Use ecc ito login --no-browser to suppress the page handoff. ECC itself does no browser automation. If the originating agent cannot complete the signed-in browser step, hand the exact command to the user; after approval finishes, return to the originating task and continue with ecc ito auth. Device tokens use macOS Keychain by default. File-token fallback is explicit and its directory and token file must remain owner-only (0700 and 0600).

  2. Run ecc ito auth to validate existing credentials; it never starts login and rejects --no-browser.

  3. Before ecc ito find, obtain explicit buyer authority to submit an RFQ.

    • Require gpu, count, whole days, max-rate, nodes, gpus-per-node, storage-tb, start-window, form-factor, contract-type, fabric, region, and the split-fill decision.
    • Require count == nodes * gpus-per-node; never derive topology.
    • Use any only when the buyer explicitly accepts any fabric or region.
    • Omitted --allow-split means false.
  4. Run the live RFQ command:

    ecc ito find \
      --gpu h200 \
      --count 8 \
      --nodes 1 \
      --gpus-per-node 8 \
      --days 30 \
      --storage-tb 1 \
      --start-window 2099-08-15 \
      --max-rate 3.00 \
      --form-factor bare_metal \
      --contract-type reservation \
      --fabric infiniband \
      --region us-east-1
    
  5. Run ecc ito status to inspect RFQs and procurement orders. After an ambiguous transport failure, check status before repeating find.

  6. When a quote is ready and the buyer explicitly approves, accept it:

    ecc ito accept rfq_<ticket-id>
    

    This routes the ticket to the desk for human review. It does not move funds or reserve capacity. Do not accept without explicit buyer authority.

  7. Run ecc ito logout when the user explicitly asks to revoke this device. The canonical CLI keeps the local credential when remote revocation fails so the operator can retry; never delete the token manually as a substitute.

Inventory prices are indicative. An RFQ is not reserved capacity. Treat a rate as fixed only when the canonical result contains a non-null firm quote.

Live node qualification

ecc ito evals exposes the canonical CLI's narrow live adapter to a separately installed sixtytwo-cli==0.3.33. It does not expose local fixture execution through ECC. Require all of the following before invoking it:

  • operator authorization to contact the named nodes;
  • ITO_ENABLE_SIXTYTWO_LIVE=1;
  • --live-sixtytwo;
  • an explicit node list; and
  • an existing absolute config directory containing sixtytwo.yaml.
ecc ito evals \
  --cluster clu_prod_example \
  --live-sixtytwo \
  --nodes gpu-01,gpu-02 \
  --config-dir /absolute/path/to/qualification-config

The canonical adapter can run only the pinned version check and sixtytwo test --full against the explicit nodes. It cannot rent, launch, recover, repair, reset, purchase, or order resources. ECC does not forward ITO_API_KEY or model/cloud credentials into node qualification.

MCP workflow

Build the canonical package, then configure the stdio server with an absolute path:

{
  "mcpServers": {
    "ito-compute": {
      "command": "node",
      "args": [
        "/absolute/path/to/ito-cloud-runtime/cli/ito-compute-cli/dist/bin/ito-mcp.js"
      ]
    }
  }
}

The server exposes only:

  • ito_auth
  • ito_find
  • ito_status
  • ito_accept

ito_auth validates existing credentials; it does not start device login. Use ito_auth, gather explicit buyer authority and every hard constraint, call ito_find, then poll with ito_status when needed. When a quote is ready and the buyer explicitly approves, call ito_accept with the ticket id. Desk quotes are usually indicative and nonbinding until the desk confirms; the result carries quote_class.

Rent or purchase semantics

find submits an RFQ and may return a firm quote, but it does not rent, purchase, reserve, provision, or move funds. accept routes a quote to the desk for human review; it does not move funds or reserve capacity. status is read-oriented, though the provider endpoint may reconcile an existing procurement order. The passive dashboard link in ECC help is a separate user-operated web route; do not open or operate it as a substitute for a missing CLI capability.

Unsupported operations

The supported client surface cannot lock quotes, reserve capacity, execute workloads, or serve inference. accept is a desk handoff, not a purchase. The MCP server does not expose qualification; use the explicit CLI command above. Do not invent additional tools or a purchase path. Do not substitute a browser or fixture when the local CLI is missing or a live operation fails. Report the missing capability and stop.

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Design and audit interfaces for Web, iOS, and Android using WCAG 2.2 accessibility guidance. Check screen-reader labels, keyboard navigation, contrast, and control sizes to identify barriers and guide implementation for people using assistive technology.

中文简介正在准备中。当前显示英语简介。

  • Adding descriptive labels to icon-only buttons
  • Reviewing keyboard navigation and modal focus
  • Checking contrast and control sizes
affaan-m/ECC28.3万2026年10月16日 更新

Investigate unreliable AI agents across 12 layers, including instructions, memory, tool execution, and display. Use code and logs to trace failures, rank findings by severity, and produce an ordered repair plan that prioritizes code changes.

中文简介正在准备中。当前显示英语简介。

  • Investigating failures that appear only inside an agent application
  • Tracing old conversation content leaking into new sessions
  • Checking skipped or falsely claimed tool execution
affaan-m/ECC28.3万2026年10月16日 更新

Compare coding agents on tasks from your own codebase. Define success checks, run agents in separate Git working directories, and report pass rates, available API costs, completion time, and consistency across repeated trials.

中文简介正在准备中。当前显示英语简介。

  • Comparing coding agents on real development tasks
  • Evaluating a new tool or model before adoption
  • Checking performance after agent updates
affaan-m/ECC28.3万2026年10月16日 更新

Design and refine an AI agent’s available actions, tool inputs, and result formats. Define recovery steps for errors, manage the information kept in context, and evaluate changes through completion rates, retries, and cost per successful task.

中文简介正在准备中。当前显示英语简介。

  • Define an AI agent’s tool set and input formats
  • Make tool results and next steps easier to interpret
  • Specify safe retries and stopping conditions
affaan-m/ECC28.3万2026年10月16日 更新

Diagnose failed AI agent runs by capturing errors, checking likely causes, and choosing small, reversible recovery actions. The workflow produces a structured report of the failure, recovery steps, and evidence, helping explain repeated retries or stalled progress.

中文简介正在准备中。当前显示英语简介。

  • Diagnosing repeated tool calls with no progress
  • Investigating quality loss as context grows
  • Checking file paths and environment mismatches
affaan-m/ECC28.3万2026年10月16日 更新

Diagnose AI agent runs that fail repeatedly, loop through tools, or lose track of the task. Capture errors and environment details, test a focused recovery action, and produce a report explaining the evidence and outcome.

中文简介正在准备中。当前显示英语简介。

  • Diagnosing repeated failures in an agent run
  • Investigating loops through the same tool calls
  • Reviewing output degradation as context grows
affaan-m/ECC28.3万2026年10月5日 更新

查看 affaan-m 的全部技能

报告此技能的问题