Results for “human-approval”

Tool lifecycle UI components for React/Next.js from ui.inference.sh. Display tool calls: pending, progress, approval required, results. Capabilities: tool status, progress indicators, approval flows, results display. Use for: showing agent tool calls, human-in-the-loop approvals, tool output. Triggers: tool ui, tool calls, tool status, tool approval, tool results, agent tools, mcp tools ui, function calling ui, tool lifecycle, tool pending

Runs a bounded spec-build-review development loop with explicit scope, stop conditions, and human approval gates for risky or ambiguous work.

Add a batteries-included agent component to React/Next.js apps with runtime, streaming, human-in-the-loop approvals, and client-side tools.

Design agents that watch data sources, build candidate prediction-market baskets, draft parameter changes, and hand results to a human for review.

Design and verify auditable human oversight, approval gates, escalation paths, and safe state transitions for AI agent workflows. Use when deciding which agent actions require review, adding approve/reject or dual-control flows, preventing unauthorized autonomous effects, creating decision records, reducing rubber-stamping, or recovering safely from rejected, expired, or failed actions.

Imported skill approval from langchain

UAT Sign-off

Improves skills by analyzing execution data to identify patterns in successful versus failed runs, staging changes for human approval.

Design, review, or troubleshoot Salesforce Approval Processes, covering entry criteria, approver routing, record locking, and recall behavior.

Iterate on a pull request until actionable CI checks pass and high/medium review feedback is addressed, stopping at human approval, draft, or merge gates.

Use when designing or auditing AI product human-in-the-loop — write approval, proposal accept/reject, action confirm, spend caps, run detail, memory capture, or any AI action with irreversible blast radius. Trigger on confirmation UX, undo, cost-before-act, show-the-plan, citations, or keeping the owner in control.

Lobster

Lobster

Give a decisive, project-grounded point of view in the subject's own shape: a graded verdict on an external-adoption question, a holistic take on a document, or a position on a user-supplied approach set. Use for a solo POV, a mid-session second opinion, a named-peer cross-check, any request to consult other models or reconcile their opinions, an `oracle` panel, or a correction-cost-gated proactive cross-check offer. Not for findings review (use ce-doc-review), neutral explainers, or generating options (use ce-ideate or ce-brainstorm).

Structures a bounded spec-build-review development loop with explicit scope, stop conditions, and human approval gates for risky or ambiguous work.

NIH grant research skill for clinical researchers. Grill-me intake (research idea + career stage + preliminary data + environment + submission posture + known institute targets) locks down the funding strategy before any search runs. Runs a 5-facet Consensus positioning analysis (with draft Significance/Innovation language), maps the research to the right NIH institutes and study sections via RePORTER, finds NOSIs and funded overlap, and produces an editable Word document (.docx) with budget/scope-aware mechanism recommendations, submission timelines, and a mandatory program officer recommendation. Use when the user asks about research funding or makes any grant-related request (e.g., 'grants for [topic]', 'find grants for my research idea', 'what grants match my research', 'help me find NIH funding', 'grant opportunities for my research'). NIH-only scope — non-NIH funders (PCORI, DOD CDMRP, VA, foundations) are out of scope and flagged at intake.

LLM-assisted human-in-the-loop review. Make sense of a change, focus attention where it matters, test. Use when the user says "checkpoint", "human review", or "walk me through this change".

去除或避免文本中的 AI 味。用于用户强制调用本 Skill，或写作/改写时提到“不要有 AI 味”“不要太假”“真情实感”“有人感”，或对已有文本/上一轮输出反馈“太像 AI”“太空泛”“太模板”“太官方”“不像我说的”等场景。

Humanization Pipeline Orchestrator v3.1 - Multi-pass 4-layer transformation pipeline Orchestrates G5 (Auditor), G6 (Humanizer), F5 (Verifier) in sequential passes Enforces checkpoints between every pass with mandatory AskUserQuestion Supports conservative (L1-2), balanced (L1-3), balanced-fast (L1-3 merged), aggressive (L1-4) modes Rich Checkpoint v2.0: section-level scores, selective humanization, target auto-stop G5+F5 parallel execution, section-selective humanization Triggers: humanize, humanize my draft, humanize manuscript, make natural, remove AI patterns Korean triggers: 휴먼화, 자연스럽게, AI 패턴 제거

LLM-assisted human-in-the-loop review. Make sense of a change, focus attention where it matters, test. Use when the user says "checkpoint", "human review", or "walk me through this change".

Acceptance-test newly added features using browser automation, happy-path flows, screenshots, UX notes, and a written report.

Consensus planning entrypoint that auto-gates vague ralph/autopilot/team requests before execution

Use when designing iOS interfaces, implementing accessibility (VoiceOver, Dynamic Type), handling dark mode, ensuring adequate touch targets, providing animation/haptic feedback, or requesting user permissions. Apple Human Interface Guidelines for iOS compliance.

Apple Human Interface Guidelines interaction and UX patterns.

飞书审批：查询和处理审批待办/已办/实例，搜索可发起审批定义、查看定义详情并发起原生审批实例。当用户要处理审批任务、查看审批实例、搜索或发起审批时使用。审批待办不是飞书任务；非审批类待办走 lark-task。不负责创建审批定义；三方审批定义不走原生提单。

Write, read, and validate HUML documents, converting between YAML/JSON/TOML and HUML for human-readable configuration files.

Walk a business/UAT approver through a plain-language demo of a verified feature and capture business acceptance signoff.

Design authentication and authorization strategy for a product or MVP. Use when the team needs sign-in methods, session model, user/workspace membership, roles, tenant boundaries, invitation flows, or permission enforcement plans.

Claims-based authorization for agents and operations. Grant, revoke, and verify permissions for secure multi-agent coordination. Use when: permission management, access control, secure operations, authorization checks. Skip when: open access, no security requirements, single-agent local work.

Writes documents in a plain, human voice and removes phrasing that reads as machine-generated, applying a two-pass write-and-audit process to any written artifact meant to be read by a person.