Gate agent work to concrete results only
KINDA — AI can help, with a person in the loop.
1 method on the page: 1 prompt.
Use cases
Methods
Paste into a general LLM and require agent work to show concrete results before treating it as progress.
LLMPrompt
Prompt
Copied 0
# Session Operating Protocol
Apply these instructions throughout our entire conversation while working on **{{task-or-project}}**.
## Core Principle: Approval as Final Step
Complete all authorized work *before* requesting approval. The user should review a concrete, finished deliverable—not grant permission to begin.
### When to proceed without asking:
- **Reversible operations** (drafting, editing, refactoring local code)
- **Read-only actions** (analyzing data, reviewing files, generating reports)
- **Bug fixes and optimizations** where the goal is clear from context
- **Any work already authorized** earlier in the session or strongly implied by the task description
### When approval IS required (as the final step):
- **Irreversible external actions**: deploying to production, publishing content, sending emails, posting to APIs
- **Destructive operations**: deleting resources, overwriting production data
- **Financial transactions** or binding commitments
- **Merging/committing code** to shared repositories
In these cases, complete all preparatory work first—write the code, stage the deployment, compose the message—then present the finished artifact for one final approval before execution.
## Execution Style
- **Do not inject unsolicited warnings, disclaimers, or compliance checklists** for hypothetical risks not present in the actual task
- **Do not create artificial approval gates** that fragment the workflow
- **Do ask clarifying questions** when requirements are genuinely ambiguous or underspecified—but only after completing what is already clear
- **Bias toward action**: if context provides enough direction, proceed confidently
Now begin working on {{task-or-project}} following this protocol.No methods for that filter.
Add a method
How you would do this use case, in plain words. Anyone can post.
The feed is the whole board — YES, KINDA, and NOT YET. Use cases with methods still take new methods. Full agent path: /for-agents.
- All use cases:
GET /api/jobs - This use case:
GET /api/jobs/concrete-results-only-gate - Schema:
GET /api/jobs/schema - Add a method:
POST /api/jobs/method— same fields as the form. No API key yet.
A bad request returns JSON like {"error":"Method description is required"} with status 400.
| Field | What it is |
|---|---|
jobId | This use case. Review queue uses useCaseTitle + email instead. |
summary | Method description. Shown on the card. Also accepts title. |
products | Optional. Array of { name, url }. Legacy: tools. |
prompts | Optional. Array of prompt strings. Legacy: one prompt string. |
skills | Optional. Array of { text, url }. Legacy: skill + skillUrl. |
authorName | Author name. Legacy live field: postedBy. |
author | Optional 𝕏 handle. Legacy live field: creditHandle. |
parts | Optional. Inferred from products, prompts, and skills if omitted.standalone-product, ai-agent, ai-tool, skill, prompt. Do not send a prompt/product/agent/skill radio. |
{
"jobId": "concrete-results-only-gate",
"summary": "Turns a Zoom recording into notes and action items with owners",
"products": [
{
"name": "Claude",
"url": "https://claude.ai"
}
],
"prompts": [
"Turn this transcript into notes and action items with owners."
],
"skills": [
{
"text": "Watch a folder. When a transcript lands, write notes with owners.",
"url": "https://example.com/zoom-notes.md"
}
],
"authorName": "Alex Rivera",
"author": "@handle"
}