By ylxmf2005
Orchestrate a multi-agent software delivery pipeline that plans, implements, reviews, and verifies code changes through specialized AI agents, automating code review, testing, and acceptance gates.
Act as the AgentCorp Acceptance Review Lead: judge whether the requirements, implementation, code review, and verification evidence are sufficient to support acceptance, and state the residual risks and release conditions. Use when running the acceptance-review phase in AgentCorp.
Act as the AgentCorp Adversarial Reviewer: challenge assumptions, surface failure modes, and stress-test requirements and designs to find overlooked risks, without rewriting the solution. Use when a high-risk, ambiguous, cross-phase, or security-sensitive decision in AgentCorp needs dedicated stress-testing.
Act as the AgentCorp API Contract Reviewer: review public/shared API surfaces, schemas, compatibility, consumer impact, auth contracts, and error semantics. Use when an API contract changes and a dedicated reviewer is needed to gate it.
Act as the AgentCorp API contract tester: write and actually run tests that verify whether an API honors its contract — request/response shape, status codes, auth/permission boundaries, error semantics, and schema consistency and compatibility. Use when an AgentCorp verification task focuses on API compatibility and contract behavior.
Use when a task needs a persistent authenticated browser session as a reusable AgentCorp behavior: set up a separate Chrome/Chromium profile with DevTools Protocol, ask the user to log in once, then run page-context JavaScript/fetch so cookies, SSO, CSRF, and same-origin behavior are real. Use for debugging, API probes, E2E or regression verification, internal web apps, authenticated smoke tests, and any task that needs real logged-in browser state without reading cookies.
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Loop engineering for software delivery: controllable, understandable, verifiable.
English · Simplified Chinese
Quick Start · Skills · Artifacts
AI can generate code faster and faster, but the cost of verifying whether that code is correct still lands on you. When you receive a pile of code that "looks fine," the responsibility for judging whether it is actually right is entirely yours. The deeper your dependency on AI becomes, the easier it is for that judgment to get dull.
The harder problem is the loop that follows: an agent's work process is a black box, so you cannot understand its reasoning; because you cannot understand it, you skip review; because you skip review, cognitive debt accumulates; the deeper that debt gets, the more dependent you become, and the harder it is to correct the agent when it goes wrong. Eventually, you no longer dare to hand it important work.
AgentCorp exists to break that loop. It is a loop engineering system for software delivery: it turns agent work from an uncontrollable, unreadable, untraceable black-box chain into a controllable, understandable, verifiable delivery loop. It includes 32 skills drawn from enterprise-grade software delivery practice, covering the full delivery loop and the supporting practices needed to run it in real projects. It works with both Claude Code and Codex.
Claude Code:
/plugin marketplace add ylxmf2005/AgentCorp
/plugin install agentcorp@agentcorp
Then run /reload-plugins or restart. Skills are namespaced, for example
/agentcorp:delivery-orchestrator.
Codex:
codex plugin marketplace add ylxmf2005/AgentCorp
Launch Codex, enable AgentCorp from the /plugins menu, and restart. To
install a single skill: use skill-installer to install the skill at repo ylxmf2005/AgentCorp path agentcorp/delivery-orchestrator.
In Claude Code, call a skill as a slash command:
/agentcorp:explain output_mode=artifact explain review/code-review.md for a sponsor
In Codex, ask for the skill by name or $skill-name:
Use $explain with output_mode=artifact to explain review/code-review.md for a sponsor.
If you omit options such as output_mode, the skill uses its default behavior.
After installation, describe what you need, or call
/agentcorp:delivery-orchestrator. It will first confirm the success criteria
with you, recommend an execution route, then move through the phases and stop at
each gate to report.
When a task needs a real browser or logged-in state verification, AgentCorp uses an isolated browser profile, asks you to log in manually once, and then performs checks inside the page automatically. It does not touch your local cookies. At the end of the task, you receive a delivery report and an audit record that traces every decision.
The 32 skills are grouped by function below. Each skill's behavior is defined in
agentcorp/<skill>/SKILL.md and appears in the Claude Code and Codex skill
pickers. Together, they cover the delivery loop and the supporting behaviors
needed to run it in real projects.
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