Human Gate Designer

What it does

When your agent uses it

• Adding approval gates
• Designing review UX
• Handling human feedback in agent workflows

Example prompts

• “human review”
• “approval gate”
• “human-in-the-loop”
• “/human-gate-designer”

Requirements

• Pre-approved tools (allowed-tools): Read, Write, Edit

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

1. 1Show context, not just output: The human needs to understand what the DAG has done so far, not just the current node's result.
2. 2Highlight decisions: Bold or annotate the choices the agent made. These are what the human is actually reviewing.
3. 3Show confidence: If the agent was uncertain, say so. Low-confidence outputs need more scrutiny.
4. 4Show cost: The human should know what they've spent and what's remaining.
5. 5Make "Modify" easy: A text input for feedback that gets injected into the retry prompt.

What it can do on your machine

Read from SKILL.md and the folder at commit 6713fc7. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves these tools, so the agent can use them without asking each time:

  • Read
  • Write
  • Edit

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  No scripts in the folder and no shell commands in SKILL.md (its code samples are mermaid).

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Human Gate Designer loads about 1.5k tokens when it runs. Until then it costs about 142 tokens; SKILL.md has 368 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~142

When it runs · the whole SKILL.md, loaded when a task matches

~1.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from curiositech/some_claude_skills at commit 6713fc7, republished under its MIT licence (© curiositech). 368 words, ~1,536 tokens.

name

human-gate-designer

description

Designs human-in-the-loop review points for DAG workflows. Determines what to present to the human, how to collect feedback, and how to route approve/reject/modify decisions back into the DAG. Use when adding approval gates, designing review UX, or handling human feedback in agent workflows. Activate on "human review", "approval gate", "human-in-the-loop", "human gate", "approval workflow", "user review step". NOT for executing human gates at runtime (use dag-runtime with Temporal signals), general UX design, or chatbot conversation design.

allowed-tools

Read, Write, Edit

metadata.category

Design & Creative

metadata.tags

human, gate, designer, human-review, approval-gate

flowchart TD
  A{Is the action irreversible?} -->|Yes| G1[Gate BEFORE the action]
  A -->|No| B{Is output user-facing?}
  B -->|Yes| G2[Gate AFTER generation, BEFORE delivery]
  B -->|No| C{Cost > $0.50 for remaining nodes?}
  C -->|Yes| G3[Gate at the cost threshold]
  C -->|No| D{Confidence score < 0.7?}
  D -->|Yes| G4[Gate on low-confidence outputs]
  D -->|No| N[No gate needed]

┌──────────────────────────────────────────────────────┐
│  🔍 Human Review: [Node Name]                        │
│                                                      │
│  Context: [1-2 sentences: what happened so far]      │
│                                                      │
│  Output to Review:                                   │
│  ┌──────────────────────────────────────────────────┐│
│  │ [The node's output, formatted for readability]   ││
│  │ [Key decisions highlighted]                      ││
│  │ [Confidence: 0.82]                               ││
│  └──────────────────────────────────────────────────┘│
│                                                      │
│  Cost so far: $0.08 / $0.50 budget                  │
│  Remaining nodes: 4 (est. $0.12)                    │
│                                                      │
│  [✅ Approve]  [✏️ Modify]  [❌ Reject]              │
│                                                      │
│  If modifying, what should change?                   │
│  ┌──────────────────────────────────────────────────┐│
│  │ [text input for human feedback]                  ││
│  └──────────────────────────────────────────────────┘│
└──────────────────────────────────────────────────────┘

flowchart TD
  H[Human decision] --> A{Decision?}
  A -->|Approve| C[Continue to next wave]
  A -->|Modify| M[Re-execute node with human feedback injected]
  M --> V[Validate modified output]
  V --> H
  A -->|Reject| R{Reject scope?}
  R -->|This node only| RN[Re-plan this node with different approach]
  RN --> H
  R -->|Entire phase| RP[Re-plan from last successful phase]
  RP --> H
  R -->|Abort DAG| AB[Stop execution, return partial results]

Original task: [same as before]
Previous output: [the output the human rejected]
Human feedback: "[the human's modification text]"

Revise your output to address the human's feedback.
Preserve the parts they didn't comment on.

© curiositech, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in .claude/skills/human-gate-designer of curiositech/some_claude_skills.

• SKILL.md
• .claude-plugin/plugin.json

Open the folder on GitHubat commit 6713fc7