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/install blocker-min-input
Description
When blocked, report exact blocker + attempts made + minimum user input needed. Enable fast unblock without back-and-forth.
README (SKILL.md)
Blocker Minimum Input
When blocked, provide everything needed for fast unblock. No back-and-forth.
Problem
Agents often:
- Say "blocked" without specifics
- Don't report what was tried
- Ask vague questions
- Require multiple clarifications
Workflow
1. Blocker Report Format
**Blocker**: Exact error/blocker text
**Attempts Made**:
- Attempt 1: what + result
- Attempt 2: what + result
**Minimum Unblock Input**: Smallest user action needed
**Fallback Option**: Alternative if user cannot unblock
2. Attempt Requirements
Before reporting blocker:
- Retry same approach with corrected parameters (1x)
- Try one fallback path
- If both fail, report with evidence
3. Minimum Input Examples
| Blocker | Minimum Input |
|---|---|
| Missing API key | Run: openclaw configure --section web |
| Permission denied | Grant write access to: D:\folder OR Use fallback: C:\workspace\folder |
| Auth failure | Check token in: openclaw.json |
Executable Completion Criteria
| Criteria | Verification |
|---|---|
| Blocker text exact | Quote error message verbatim |
| Attempts listed | At least 2 attempts documented |
| Minimum input specific | Single command or action |
| Fallback provided | Alternative path exists |
Privacy/Safety
- No credentials in blocker reports
- Redact tokens/keys from error messages
- Use generic paths when sensitive
Self-Use Trigger
Use when:
- Any tool call fails twice
- User input required to proceed
- Permission/auth issues detected
One report. One input. Unblock fast.
Usage Guidance
This skill appears coherent and low-risk: it only contains instructions for how an agent should report blockers and asks for no credentials or installs. Before enabling, consider two practical safeguards: (1) configure the agent to confirm with the user before retrying commands that might change state (to avoid unintentional destructive retries); (2) ensure the agent implements robust redaction when quoting error messages (errors can sometimes include tokens or sensitive paths). If you want stricter behavior, request the skill be modified to refuse automatic retries on potentially unsafe commands and to use a clear redaction routine for secrets.
Capability Analysis
Type: OpenClaw Skill
Name: blocker-min-input
Version: 1.0.0
The skill `blocker-min-input` is designed to improve an AI agent's reporting when it encounters a blocker. The `SKILL.md` file provides instructions for the agent to format blocker reports with specific details like exact error text, attempts made, minimum user input needed, and fallback options. Crucially, it includes explicit 'Privacy/Safety' guidelines instructing the agent to redact tokens/keys and avoid credentials in reports. There is no evidence of malicious intent, data exfiltration, unauthorized execution, or prompt injection designed to subvert the agent for harmful purposes; instead, the instructions aim to enhance helpfulness and safety.
Capability Assessment
Purpose & Capability
The name/description promise (report exact blocker, attempts, and minimum input) matches the instructions in SKILL.md. The file-only, instruction-only nature and absence of env vars/binaries/install spec are proportionate to the claimed functionality. Examples referencing openclaw CLI/config are reasonable for an agent-internal unblock helper.
Instruction Scope
Instructions are narrowly focused on retrying once, trying one fallback, and reporting evidence, which stays within the stated purpose. Two cautions: (1) automatic retrying of commands may have side effects if the command is destructive — the skill does not require the agent to confirm with the user before re-running potentially state-changing operations; (2) quoting error messages verbatim can accidentally expose secrets if errors include tokens — the SKILL.md says to redact tokens but does not specify how to reliably detect/redact them. These are operational precautions rather than evidence of malice.
Install Mechanism
No install spec, no code files — instruction-only reduces risk because nothing is written to disk or fetched at install time.
Credentials
The skill requests no environment variables, credentials, or config paths. Examples mention openclaw.json and CLI commands as user actions, but the skill does not ask the agent to read secrets or require platform credentials.
Persistence & Privilege
always:false and no hooks to modify other skills or system config. The skill can be invoked by the agent, which is the platform default and acceptable here.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install blocker-min-input - After installation, invoke the skill by name or use
/blocker-min-input - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release with clear blocker reporting for faster unblocking.
- Standardized "Blocker Report" format: exact error, attempts made, minimum user input, and fallback.
- Agents must try at least two solutions before reporting a blocker.
- Reports include specific minimum input and an alternative option.
- Privacy measures: redact credentials and sensitive paths from all outputs.
Metadata
Frequently Asked Questions
What is Blocker Minimum Input?
When blocked, report exact blocker + attempts made + minimum user input needed. Enable fast unblock without back-and-forth. It is an AI Agent Skill for Claude Code / OpenClaw, with 327 downloads so far.
How do I install Blocker Minimum Input?
Run "/install blocker-min-input" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Blocker Minimum Input free?
Yes, Blocker Minimum Input is completely free (open-source). You can download, install and use it at no cost.
Which platforms does Blocker Minimum Input support?
Blocker Minimum Input is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Blocker Minimum Input?
It is built and maintained by Dalomeve (@dalomeve); the current version is v1.0.0.
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