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consensus-agent-action-guard

Pre-execution governance for high-risk agent actions. Uses persona-weighted consensus to decide ALLOW/BLOCK/REQUIRE_REWRITE before external or irreversible s...

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Pre-execution governance for high-risk agent actions. Uses persona-weighted consensus to decide ALLOW/BLOCK/REQUIRE_REWRITE before external or irreversible s...

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Install for OpenClaw

Quick setup
  1. Download the package from Yavira.
  2. Extract the archive and review SKILL.md first.
  3. Import or place the package into your OpenClaw setup.

Requirements

Target platform
OpenClaw
Install method
Manual import
Extraction
Extract archive
Prerequisites
OpenClaw
Primary doc
SKILL.md

Package facts

Download mode
Yavira redirect
Package format
ZIP package
Source platform
Tencent SkillHub
What's included
AI-SELF-IMPROVEMENT.md, README.md, SKILL.md, examples/input.json, metadata.json, package-lock.json

Validation

  • Use the Yavira download entry.
  • Review SKILL.md after the package is downloaded.
  • Confirm the extracted package contains the expected setup assets.

Install with your agent

Agent handoff

Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.

  1. Download the package from Yavira.
  2. Extract it into a folder your agent can access.
  3. Paste one of the prompts below and point your agent at the extracted folder.
New install

I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.

Upgrade existing

I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.

Trust & source

Release facts

Source
Tencent SkillHub
Verification
Indexed source record
Version
1.1.14

Documentation

ClawHub primary doc Primary doc: SKILL.md 11 sections Open source page

consensus-agent-action-guard

consensus-agent-action-guard is the final safety gate before autonomous action execution.

What this skill does

evaluates proposed agent actions (risk, irreversibility, side effects) applies hard-block and weighted consensus logic returns one of: ALLOW | BLOCK | REQUIRE_REWRITE emits required follow-up actions (e.g., human confirmation) writes decision and persona updates to board artifacts

Why this matters

Most catastrophic automation failures happen at execution time. This skill inserts explicit governance before side effects.

Ecosystem role

Built on the same consensus stack as communication and merge guards, giving one policy language across agent operations.

Typical usage

gating destructive operations controlling external messaging/posting actions requiring human confirmation for irreversible high-risk tasks

Runtime, credentials, and network behavior

runtime binaries: node, tsx network calls: none in the guard decision path itself filesystem writes: board/state artifacts under the configured consensus state path

Dependency trust model

consensus-guard-core is the first-party consensus package used in guard execution versions are semver-pinned in package.json for reproducible installs this skill does not request host-wide privileges and does not mutate other skills

Quick start

node --import tsx run.js --input ./examples/input.json

Tool-call integration

This skill is wired to the consensus-interact contract boundary (via shared consensus-guard-core wrappers where applicable): readBoardPolicy getLatestPersonaSet / getPersonaSet writeArtifact / writeDecision idempotent decision lookup This keeps board orchestration standardized across skills.

Invoke Contract

This skill exposes a canonical entrypoint: invoke(input, opts?) -> Promise<OutputJson | ErrorJson> invoke() starts the guard flow and executes deterministic policy evaluation with board operations via shared guard-core wrappers.

external_agent mode

Guards support two modes: mode="external_agent": caller supplies external_votes[] from agents/humans/models for deterministic aggregation. mode="persona": requires an existing persona_set_id; guard will not generate persona sets internally.

Category context

Agent frameworks, memory systems, reasoning layers, and model-native orchestration.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package
3 Docs3 Config
  • SKILL.md Primary doc
  • AI-SELF-IMPROVEMENT.md Docs
  • README.md Docs
  • examples/input.json Config
  • metadata.json Config
  • package-lock.json Config