resume

resume is a command for coding agents from indranilbanerjee/contentforge. It costs 12 tokens per session (1,960 once invoked), scanned A, original, MIT.

A command for continuing an interrupted ContentForge content-generation pipeline. It reloads saved checkpoints so the pipeline can continue from the last completed phase instead of starting over.

In plain words
What is it for?
Use it with an optional run ID to resume a saved run, skip completed phases, or continue any phase marked for rework.
Why use it?
It recovers work lost when an agent session ends because of a timeout, network problem, cancellation, or sleeping computer.

Command

Installs and runs on its own, but its text points at files inside its plugin — anything it tells you to read at a ${CLAUDE_PLUGIN_ROOT} path is only there once the plugin is installed. Installing the plugin gets both.

Part of the contentforge plugin — 22 skills, 9 commands, 13 agents 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/indranilbanerjee/contentforge/resume
Clone the repo
git clone --depth 1 https://github.com/indranilbanerjee/contentforge

Or install contentforge, the plugin that ships this one along with the rest of its 22 skills, 9 commands, 13 agents.

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 resume

README.md
[![agentmods](https://agentmods.dev/badge/commands/indranilbanerjee/contentforge/resume.svg)](https://agentmods.dev/commands/indranilbanerjee/contentforge/resume)
Your own site
<a href="https://agentmods.dev/commands/indranilbanerjee/contentforge/resume"><img src="https://agentmods.dev/badge/commands/indranilbanerjee/contentforge/resume.svg" alt="Measured on agentmods" height="20"></a>
Per session 12 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,960 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 $0.00012 $0.01960
Opus 5 $0.00006 $0.00980
Sonnet 5 $0.00002 $0.00392
Haiku 4.5 $0.00001 $0.00196

Measured 4d ago against content hash 12c63666ed5d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

resume 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 4d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

  • resume — 100% identical, 0 lines differ
commands/resume.md · 128 lines

How it starts

The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Resume Interrupted Pipeline

Pick up a /contentforge:create-content run that stopped before Phase 8 finished — instead of restarting from scratch, load the run manifest and continue from the next phase (or the pending rework target).

Trigger

User runs /contentforge:resume (with optional run-id argument). Also surface this command in any error message when a pipeline run terminates abnormally.

What this fixes

ContentForge's 10-phase pipeline is long-running. If the underlying agent session terminates partway through (context-window exhaustion, network blip, user cancels, machine sleeps), the in-memory Phase 1-N outputs disappear. Every phase that passes its quality gate writes its output to ~/.claude-marketing/{brand-slug}/runs/{run_id}/ via scripts/checkpoint-manager.py, so a fresh session can reload those artifacts and skip the phases that already completed.

Process

Step 0: Cross-session checkpoint download (Cowork only)

Before listing local runs, check if we're in Cowork+Drive mode — if so, the user might be resuming from a DIFFERENT Cowork session (different sandbox), and the local FS has no record of the run. Pull the run's checkpoint state from Drive first.

python ${CLAUDE_PLUGIN_ROOT}/scripts/drive-sync-state.py --action read-config

If configured: false OR environment != "cowork-sandbox", skip to Step 1 (local-mode flow).

If configured: true AND a Drive MCP is available:

  1. Use the Drive MCP to list contents of {drive_root_folder_name}/_runs/
  2. For each <run_id> subfolder, check if it has phase artifacts (phase-*.md, _manifest.json, _sync-pending.json)
  3. Identify in-progress runs (manifest exists but phase_artifacts doesn't include phase 8 — i.e., output-manager hasn't completed)
  4. For each in-progress run that doesn't yet exist locally at ~/.claude-marketing/{brand-slug}/runs/{run_id}/:
    • Use the Drive MCP to download every file from {drive_root}/_runs/{run_id}/ into the local sandbox path
    • This restores the run's full checkpoint history so Step 2 below can load artifacts normally
  5. Tell the user: "Pulled {N} run(s) from Drive for resume eligibility: {run_id list}"

Read the full file on GitHub · 128 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. 4d ago First seen · 128 lines · 12 tokens per session scan A 12c63666ed5d

Subscribe to this mod's changes

resume is a command published in the GitHub repository indranilbanerjee/contentforge (26 stars, last pushed 18d ago), licensed MIT. It adds 12 tokens to every session and 1,960 once invoked, about $0.0001 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 2026-08-30.

Related

Other commands, from other repositories

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resume

Resume a long-running DMP workflow (engagement / campaign-plan / content-engine / seo-audit / competitor-analysis / campaign-audit / launch-campaign) that was interrupted partway through.

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output-folder

Print + open the user-visible DMP output folder for a brand (/Documents/DigitalMarketingPro/{brand}/). Direct answer to "where did my engagement deliverables save?".

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Run the unified pre-publish quality gate on marketing content (hallucination + brand voice + structure + claims). Use before publishing any marketing copy.

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doctor

Per-action readiness diagnostic. Shows which campaign-audit and launch-campaign actions are live (manifest-ready) vs blocked (stub-unconfigured) in the current environment, with one-step setup hints for the blocked ones. Now includes model-registry freshness + Cowork+Drive routing status.

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