How do I install the Consensus Persona Respawn skill?

Run npx skillmds@latest add modbender/consensus-persona-respawn in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Consensus Persona Respawn safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: executes scripts. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Consensus Persona Respawn?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Consensus Persona Respawn free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Consensus Persona Respawn?

modbender (@modbender) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Consensus Persona Respawn by modbender

Name: Consensus Persona Respawn
Rating: 4.2 (5 reviews)
Author: modbender

Consensus Persona Respawn

Ledger-informed persona lifecycle management. Replaces low-performing personas with successor personas derived from mistake patterns in board decision history, preserving adaptive governance over long-running automation. Reputation updates are computed by consensus-persona-engine.

modbender Updated Sep 9, 2026 12 repo stars

File contents

consensus-persona-respawn

consensus-persona-respawn is the adaptive maintenance loop for persona governance.

What this skill does

identifies dead/weak personas by trigger or reputation threshold
mines historical decision artifacts for mistake patterns
generates successor persona profiles informed by those failures
writes persona_respawn and updated persona_set artifacts
keeps governance panel quality from stagnating

Why this matters

A static evaluator panel drifts over time. This skill provides lifecycle renewal so consensus quality improves instead of degrading.

Ecosystem role

Consumes persona-engine outputs for long-term adaptation and ties directly into board-ledger evidence.

Best use cases

long-running agent teams
recurring decision domains with repeated failure classes
autonomous systems requiring evaluator maintenance

Runtime and network behavior

runtime binaries: node, tsx
network calls: none in shipped respawn logic
environment config read by this package: CONSENSUS_STATE_FILE, CONSENSUS_STATE_ROOT
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 runtime 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

Install

npm i consensus-persona-respawn

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() executes persona replacement based on lineage and failure patterns. Reputation deltas are expected from consensus-persona-engine outputs.

---name: consensus-persona-respawndescription: Ledger-informed persona lifecycle management. Replaces low-performing personas with successor personas derived from mistake patterns in board decision history, preserving adaptive governance over long-running automation. Reputation updates are computed by consensus-persona-engine.--- # consensus-persona-respawn `consensus-persona-respawn` is the adaptive maintenance loop for persona governance. ## What this skill does - identifies dead/weak personas by trigger or reputation threshold - mines historical decision artifacts for mistake patterns - generates successor persona profiles informed by those failures - writes `persona_respawn` and updated `persona_set` artifacts - keeps governance panel quality from stagnating ## Why this matters A static evaluator panel drifts over time. This skill provides lifecycle renewal so consensus quality improves instead of degrading. ## Ecosystem role Consumes persona-engine outputs for long-term adaptation and ties directly into board-ledger evidence. ## Best use cases - long-running agent teams - recurring decision domains with repeated failure classes - autonomous systems requiring evaluator maintenance ## Runtime and network behavior - runtime binaries: `node`, `tsx` - network calls: none in shipped respawn logic - environment config read by this package: `CONSENSUS_STATE_FILE`, `CONSENSUS_STATE_ROOT` - 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 runtime 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 ## Install ```bash npm i consensus-persona-respawn ``` ## Quick start ```bash 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()` executes persona replacement based on lineage and failure patterns. Reputation deltas are expected from consensus-persona-engine outputs.

Frequently asked questions