rekindle

rekindle is a command for coding agents from justinjdev/fellowship. It costs 43 tokens per session (1,862 once invoked), scanned A, original, Apache-2.0.

A recovery command for restarting a fellowship after a crashed or expired session by examining its saved workspaces and state files.

In plain words
What is it for?
Use it to scan previous fellowship artifacts, classify the remaining quests, and resume the coordinator with recovered context.
Why use it?
It helps recover unfinished coordinated work without losing track of completed, active, or abandoned tasks.

Command

Part of the fellowship plugin — 20 skills, 19 commands, 6 agents, 3 hooks shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add commands/justinjdev/fellowship/rekindle
Clone the repo
git clone --depth 1 https://github.com/justinjdev/fellowship

Or install fellowship, the plugin that ships this one along with the rest of its 20 skills, 19 commands, 6 agents, 3 hooks.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for rekindle

README.md
[![agentmods](https://agentmods.dev/badge/commands/justinjdev/fellowship/rekindle.svg)](https://agentmods.dev/commands/justinjdev/fellowship/rekindle)
Your own site
<a href="https://agentmods.dev/commands/justinjdev/fellowship/rekindle"><img src="https://agentmods.dev/badge/commands/justinjdev/fellowship/rekindle.svg" alt="Measured on agentmods" height="20"></a>
Per session 43 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,862 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00043 $0.01862
Opus 5 $0.00022 $0.00931
Sonnet 5 $0.00009 $0.00372
Haiku 4.5 $0.00004 $0.00186

Measured 3d ago against content hash 19ebb9098f59, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

rekindle scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugin/commands/rekindle.md · 174 lines

How it starts

The opening of the file, as written. The whole thing — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Rekindle — Fellowship Crash Recovery

Overview

Reconstructs fellowship state from on-disk artifacts after a session crash and transitions into Gandalf coordinator mode with recovered context. The flame that was quenched can be rekindled.

When to Use

  • Session crashed or context window filled up during a fellowship
  • User returns to find scattered worktrees from a previous fellowship
  • User invokes /rekindle directly

Process

Note: .fellowship/ is the default data directory. Users can override it via dataDir in ~/.claude/fellowship.json. All fellowship CLI commands and paths below use the configured data directory automatically.

Step 1: Scan

Run the CLI to discover fellowship artifacts:

fellowship status --json

This scans all git worktrees for .fellowship/quest-state.json files, checks for checkpoints (.fellowship/checkpoint.md), detects merged branches, and reads .fellowship/fellowship-state.json from the main repo.

If no quests are found, report: "There is nothing to rekindle. The ashes have gone cold." and stop.

Step 2: Classify

Each quest gets one classification:

Classification Condition Action
Complete Branch merged into main Skip — already shipped
Resumable Has .fellowship/checkpoint.md Continue from current phase with checkpoint context
Stale No checkpoint Restart current phase from scratch

Step 3: Present Recovery Dashboard

Show the user what was found:

The flame that was quenched can be rekindled.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

quest-api-auth    │ Implement (checkpoint ✓) │ Resumable
quest-db-schema   │ Plan      (checkpoint ✓) │ Resumable
quest-ui-login    │ Research  (no checkpoint) │ Restart phase

Merged (skipping):
  fellowship/config-fix (branch merged into main)

Proceed with recovery? (y/n)

If the user declines, stop. Do not proceed without confirmation.

Step 4: Re-spawn Fellowship

On user confirmation, transition into Gandalf coordinator mode:

Read the full file on GitHub · 174 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 174 lines · 43 tokens per session scan A 19ebb9098f59

Subscribe to this mod's changes

rekindle is a command published in the GitHub repository justinjdev/fellowship (5 stars, last pushed 20d ago), licensed Apache-2.0. It adds 43 tokens to every session and 1,862 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other commands, from other repositories

auto-mode

Idea-to-running-code lifecycle orchestration. 10-phase pipeline with 5 hard decision gates, wave-based parallelism, and STATE.json resumability. Composes /deep-research, /auto-swarm-nth, /production-upgrade, /security-audit, and /ship into a single end-to-end flow.

ShaheerKhawaja/ProductionOS · 68 tokens

max-research

Nuclear-scale autonomous research — deploys 500-1000 agents in ONE massive simultaneous wave for exhaustive topic saturation. Deep-research methodology × auto-swarm scale = maximum parallel intelligence. WARNING: Extreme resource consumption.

ShaheerKhawaja/ProductionOS · 48 tokens

omni-plan

ProductionOS flagship — 13-step orchestrative pipeline with tri-tiered evaluation, recursive convergence, CEO/Eng/Design review chain, CLEAR framework evaluation, multi-model judge tribunal, and autonomous PIVOT/REFINE/PROCEED decisions. Targets 100% production-ready output.

ShaheerKhawaja/ProductionOS · 62 tokens

auto-swarm-nth

Nth-iteration agent swarm — spawns parallel agent waves, evaluates strictly per wave, re-swarms gaps until 100% coverage and 10/10 quality. Can invoke any ProductionOS skill or command within waves.

ShaheerKhawaja/ProductionOS · 51 tokens

frontend-upgrade

Full-stack frontend upgrade pipeline — fuses /production-upgrade iterative audit with /plan-ceo-review vision and /plan-eng-review rigor. Deploys parallel auto-swarm agents for iterative audit and execution. Enriched with /deep-research for competitive parity.

ShaheerKhawaja/ProductionOS · 56 tokens

omni-plan-nth

Nth-iteration omni-plan — recursive orchestration that chains ALL ProductionOS skills and agents, evaluates strictly per iteration, and loops until 10/10 is achieved. Each iteration can invoke any command or skill in the system.

ShaheerKhawaja/ProductionOS · 51 tokens