20 docs tagged with "coding-assistant"

Audit an Agent Skills loadout with specification checks, catalog budgets, overlap detection, near-miss prompts, and real activation records.

Build an evidence-based AI code review workflow that checks intent, runtime behavior, tests, risk boundaries, and the latest diff before merge.

A practical beginner route for choosing an AI coding agent, writing safe prompts, using Git checkpoints, reviewing diffs, running checks, and understanding tool roles.

A beginner guide to Claude Code: when to use it, how to install it, how to write your first task, review diffs, run checks, and keep Git checkpoints.

A beginner guide to OpenAI Codex across the app, IDE extension, CLI, and cloud workflows, with safe prompting, AGENTS.md, planning, tests, and review habits.

Build a fair 3–5-task pilot to compare Coding Agents on your repository with fixed commits, tests, permissions, budgets, repeated trials, and review burden.

Learn what a Coding Agent should verify in a real browser before trusting a UI patch: layout, network, console, session state, and evidence limits.

Turn a preserved Coding Agent trace into a local JSONL dataset, deterministic graders, machine-readable reports, and a CI quality gate.

Understand how a coding agent harness controls repository context, tools, orchestration, sandbox boundaries, memory, verification, and agent selection.

Learn how to separate coding-agent memory into durable project rules, active task state, retrievable history, and disposable working context.

Build a local Coding Agent trace audit that preserves tool failures, retries, Token usage, handoffs, and explicit telemetry gaps.

Understand coding agent sandbox boundaries, workspace-write risks, host trust, command allowlists, privileged daemons, and practical isolation checks.

Run a reproducible Copilot CLI 1.0.94 lab to compare local sandbox policies, offline mode, file access, and tool-network access.

Set up DeepSeek V4-Flash in Codex CLI with a model catalog, named profile, API key, verification, rollback, and Responses API compatibility limits.

Design a Coding Agent Graph with explicit dependencies, serial and parallel execution, typed signals, merge rules, escalation, and governor authority.

Run parallel Coding Agents with isolated worktrees, runtime state, evidence, and merge authority so concurrency does not become integration chaos.

Verify AI-generated Go code with a reproducible Go workflow covering build, tests, vet, fuzzing, govulncheck, and human review.

Install Kimi Code CLI, migrate safely from the legacy Kimi CLI, verify configuration, understand permission modes, and run a careful first task.

Review dependent coding-agent changes with a local Git and Python lab: isolate layer diffs, catch semantic regressions after rebase, and repair squash-merge baselines.

Build a bounded Coding Agent Loop with an explicit local aim, evaluator, budget, stopping condition, authority scope, and escalation path.