Resume Check — AI Coding Handoffs

Give your next coding agent a checked starting point.

Resume Check V2 — 0.2.0 beta

When a coding session ends, the next agent needs to know what you were doing, what changed, and what still needs checking. Resume Check saves that handoff in your local Git project and checks it when you return.

What you get

• A startup brief with the current role, task, recorded progress, and next step.
• Warnings about changed project files, missing instructions, stale checkpoints, and unresolved actions.
• Closeout checks for the work and progress files you configure, so the next session has an explicit record of what was updated or left unchanged.

Before you buy

Requires an AI coding environment that can read local files and run shell commands, a local Git repository with an initial commit, Python 3.10+, and Git. Chat-only interfaces cannot run the checker. You must configure the project and save checkpoints deliberately.

How you use it

1. Connect your coding agent to Agensi and load Resume Check with get_skill. Load the current approved instructions when you use the skill in a new session.
2. Your agent reads the delivered script, guides and examples in memory. It runs the unchanged Python script through python3 - with the script on standard input, without saving the package files.
3. Configure your project profile, required instructions, current task and closeout files. Your project-specific records and checkpoints stay in your Git project.
4. Save a checkpoint before ending a coding session. When you return, inspect the handoff and read the startup brief. Resolve flagged issues before continuing authorized work.

Included

10 functional text-file contents through Agensi MCP: skill instructions, a Python command-line tool, agent configuration, an operating guide, a format reference, and five JSON examples for the profile, current work, checkpoint, source review, and closeout. No icon is required to run the checker.

Tested beta

63 automated checks passed: 34 V1 regressions and 29 V2 checks. Two synthetic fresh-agent trials passed: one completed the current local task; the other stopped on a missing required instruction and preserved an unresolved action.

Creator-access delivery and execution through Agensi MCP were also tested on 2026-10-12 using only Agensi-delivered materials. The unchanged script ran through standard input without being saved. The executed V2 configuration, checkpoint/review, file drift, missing required source, unresolved action and closeout scenarios passed.

Tested on Linux with Python 3.12.14 and Git 2.51.1. Ordinary paid-buyer checkout, entitlement and delivery remain unverified. No customer pilot or cross-platform claim.

Limits

Checkpoints must be saved and required sources listed explicitly. The tool cannot recover unsaved chats, extend a model's context window, automatically import an existing YAML workflow, execute saved instructions, retry external actions, or sync to the cloud.

Source-review receipts are agent self-reports. Closeout checks compare file changes, not semantic correctness. Passing checks do not prove claims are true or grant permission to act. V1 state can be upgraded explicitly with a backup while preserving unresolved journal entries.

Privacy and purchase

The Python tool runs locally with no built-in network calls or telemetry. Your AI coding environment may have its own data-handling settings.

$19 one-time purchase. Access is managed through Agensi. No hosted service or subscription.