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terminal-ops

Evidence-first repo execution workflow for ECC. Use when the user wants a command run, a repo checked, a CI failure debugged, or a narrow fix pushed with exact proof of what was executed and verified.

terminal-ops 是什么?

terminal-ops is a Claude Code agent skill that evidence-first repo execution workflow for ECC. Use when the user wants a command run, a repo checked, a CI failure debugged, or a narrow fix pushed with exact proof of what was executed and verified.

兼容平台~Claude Code~Codex CLI~Cursor
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Terminal Ops

Use this when the user wants real repo execution: run commands, inspect git state, debug CI or builds, make a narrow fix, and report exactly what changed and what was verified.

This skill is intentionally narrower than general coding guidance. It is an operator workflow for evidence-first terminal execution.

Skill Stack

Pull these ECC-native skills into the workflow when relevant:

  • verification-loop for exact proving steps after changes
  • tdd-workflow when the right fix needs regression coverage
  • security-review when secrets, auth, or external inputs are involved
  • github-ops when the task depends on CI runs, PR state, or release status
  • knowledge-ops when the verified outcome needs to be captured into durable project context

When to Use

  • user says "fix", "debug", "run this", "check the repo", or "push it"
  • the task depends on command output, git state, test results, or a verified local fix
  • the answer must distinguish changed locally, verified locally, committed, and pushed

Guardrails

  • inspect before editing
  • stay read-only if the user asked for audit/review only
  • prefer repo-local scripts and helpers over improvised ad hoc wrappers
  • do not claim fixed until the proving command was rerun
  • do not claim pushed unless the branch actually moved upstream

Workflow

1. Resolve the working surface

Settle:

  • exact repo path
  • branch
  • local diff state
  • requested mode:
    • inspect
    • fix
    • verify
    • push

2. Read the failing surface first

Before changing anything:

  • inspect the error
  • inspect the file or test
  • inspect git state
  • use any already-supplied logs or context before re-reading blindly

3. Keep the fix narrow

Solve one dominant failure at a time:

  • use the smallest useful proving command first
  • only escalate to a bigger build/test pass after the local failure is addressed
  • if a command keeps failing with the same signature, stop broad retries and narrow scope

4. Report exact execution state

Use exact status words:

  • inspected
  • changed locally
  • verified locally
  • committed
  • pushed
  • blocked

Output Format

SURFACE
- repo
- branch
- requested mode

EVIDENCE
- failing command / diff / test

ACTION
- what changed

STATUS
- inspected / changed locally / verified locally / committed / pushed / blocked

Pitfalls

  • do not work from stale memory when the live repo state can be read
  • do not widen a narrow fix into repo-wide churn
  • do not use destructive git commands
  • do not ignore unrelated local work

Verification

  • the response names the proving command or test
  • git-related work names the repo path and branch
  • any push claim includes the target branch and exact result

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/content-engine

Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.

affaan-m/fal-ai-media

Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

affaan-m/manim-video

日本語翻訳:このファイルは manim-video 用の日本語翻訳が必要です

affaan-m/remotion-video-creation

Remotion のベストプラクティス - React で動画を作成する。3D、アニメーション、音声、字幕、チャート、トランジションなどをカバーするドメイン固有の29のルール。

affaan-m/video-editing

AI-assisted video editing workflows for cutting, structuring, and augmenting real footage. Covers the full pipeline from raw capture through FFmpeg, Remotion, ElevenLabs, fal.ai, and final polish in Descript or CapCut. Use when the user wants to edit video, cut footage, create vlogs, or build video content.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

agent-self-evaluation

Use after completing any non-trivial task. The agent self-rates its output on 5 axes — accuracy, completeness, clarity, actionability, conciseness — with concrete evidence per criterion. Produces a structured 1-5 scorecard with specific improvement suggestions.

agent-sort

Build an evidence-backed ECC install plan for a specific repo by sorting skills, commands, rules, hooks, and extras into DAILY vs LIBRARY buckets using parallel repo-aware review passes. Use when ECC should be trimmed to what a project actually needs instead of loading the full bundle.

ai-first-engineering

Engineering operating model for teams where AI agents generate a large share of implementation output. Use when setting team process, review gates, or ownership rules for a codebase largely written by agents.

ai-regression-testing

Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code. Use when adding regression coverage to AI-assisted code, or when the same model both wrote and reviewed a change.

android-clean-architecture

Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns. Use when structuring modules, layers, or data flow in an Android or KMP project.

angular-developer

Generates Angular code and provides architectural guidance. Trigger when creating projects, components, or services, or for best practices on reactivity (signals, linkedSignal, resource), forms, dependency injection, routing, SSR, accessibility (ARIA), animations, styling (component styles, Tailwind CSS), testing, or CLI tooling.

api-connector-builder

Build a new API connector or provider by matching the target repo

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