菜单
Submit, list, resolve, close, or delete Atris customer feedback. Use when user types /feedback or asks to triage the feedback queue.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | atris-feedback |
| description | Submit, list, resolve, close, or delete Atris customer feedback. Use when user types /feedback or asks to triage the feedback queue. |
| version | 1.0.0 |
| tags | ["feedback","customer","admin"] |
One skill for everything: submit feedback, view the queue, resolve/close/delete items.
atris feedback CLI command from the reference belowatris CLI is unavailable, fall back to the direct API/DynamoDB path/feedback (no args) → show the queue/feedback <message> → submit new feedback/feedback resolve <id> <resolution> → mark as resolved, notify customer/feedback close <id> → close as wontfix/duplicate/feedback delete <id> → remove from queueThe atris CLI wraps every feedback operation against the production API and
handles auth from the user's login. Use it first — it's the canonical,
audited path and works without needing AWS credentials.
atris feedback # list queue
atris feedback "the calendar hangs" # submit
atris feedback resolve abc123 "fixed" # mark resolved
atris feedback close abc123 # close as wontfix
atris feedback delete abc123 # delete
IDs can be short (first 8 chars of the UUID) — the CLI resolves the prefix against the live list before acting.
If atris is not on PATH, it lives at ~/arena/atris-cli/bin/atris.js.
Only use this path if the CLI is unavailable (stale install, broken login).
Use this only from a trusted service workspace with AWS credentials already configured. Do not ask end users to clone or run backend services locally.
from dotenv import load_dotenv; load_dotenv('backend/.env')
import boto3
table = boto3.resource('dynamodb', region_name='us-east-1').Table('atris_feedback')
curl -s -X POST "https://api.atris.ai/api/feedback" \
-H "Content-Type: application/json" \
-H "X-Feedback-Key: $FEEDBACK_API_KEY" \
-d '{"message": "THE_MESSAGE", "source": "cli", "context": {"user_email": "GIT_EMAIL"}}'
Confirm: Feedback submitted (id: abc123)
table.update_item(
Key={'id': FULL_ID},
UpdateExpression='SET #s = :s, resolution = :r, resolved_at = :t',
ExpressionAttributeNames={'#s': 'status'},
ExpressionAttributeValues={':s': 'resolved', ':r': RESOLUTION, ':t': NOW},
)
Print: Resolved abc123: <resolution>
Same as resolve but status = 'closed', no resolution text needed.
table.delete_item(Key={'id': FULL_ID})
Print: Deleted abc123
Users type short IDs (first 8 chars). Scan the table and match by prefix to find the full UUID.
Always print the result directly as text. Never leave it inside a tool call expansion.
Frontend aesthetics policy. Use when building UI, components, landing pages, dashboards, or any frontend work. Prevents generic ai-generated look.
Backward partner to /flow. Picks the next horizon from inbox + wiki + lessons, writes the reverse path as tagged tasks to TODO.md so /autopilot can pursue it tick by tick. Triggers on: endgame, what's the last move, where are we heading, reverse engineer, work backward.
Run one verified, scored improvement tick and write its receipt. Use when the user asks to improve, make this better, ship one thing, run a tick, or get smarter. `atris improve` alone shows metabolism vitals; use `atris improve tick` to ship work.
Dispatch coding work to an installed terminal agent — Codex, Cursor, Devin, Grok, or Atris Fast — as an interchangeable worker engine. Claude orchestrates: writes the bounded prompt, the engine builds, Claude verifies and lands. Triggers on: use codex, use cursor, use devin, use grok, use atris, engine, dispatch to, worker agent, second opinion build.
Working method distilled from Claude Fable 5 for daily-driver models (Opus, Sonnet). Use at session start, before any multi-step task, or when output feels shallow, hedged, or prematurely "done". Triggers on fable method, think like fable, deep pass.
Use the Render.com CLI v2.x (`render`) to inspect Render services, check CLI auth, list services and deploys, trigger deploys when explicitly requested, and view logs. Use when an agent needs Render CLI commands, non-interactive flags, deploy status polling, or service auto-deploy checks.