Skip to main content
Glama

checkpoint

Destructive

Save a durable progress checkpoint capturing summary and git state, updating status and next actions for the next session. Use after meaningful progress, before ending, or before risky changes.

Instructions

Save a durable progress checkpoint under .agentpack/checkpoints, capturing summary and git state (branch, commit, diff) and updating the pack-level status and next actions that seed the next session's load_context. Call after meaningful progress, before ending a session, or before risky changes — not after every small step.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusNoCurrent overall status line, replacing the previous one.
summaryNoWhat was accomplished and decided since the last checkpoint.
nextActionsNoConcrete next steps, replacing the previous list when non-empty.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare destructiveHint=true, and the description adds useful context: the checkpoint is durable, captures git state, updates pack-level status/next actions, and seeds the next session's load_context. It does not contradict annotations and provides behavioral detail beyond the structured fields.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single dense sentence that front-loads the action and resource, then provides usage timing. Every phrase adds value, with no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and three well-documented parameters, the description covers purpose, side effects, and usage timing. It could mention what the return value is or explicitly state that previous checkpoints are overwritten, but the schema hints at 'replacing' and the overall context is sufficient for an agent to use the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% for all three parameters, so the schema already explains them thoroughly. The description reinforces that status and nextActions get updated, but does not add meaning beyond the schema, meeting the baseline of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific verb ('Save') and resource ('.agentpack/checkpoints'), and details what is captured (summary and git state) and updated (pack-level status and next actions). This distinguishes it from sibling tools like load_context by explicitly noting it seeds the next session's load_context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly states when to use the tool ('after meaningful progress, before ending a session, or before risky changes') and when not to use it ('not after every small step'). This provides strong usage guidance, even though it does not name alternative tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ihorponom/agentpack'

If you have feedback or need assistance with the MCP directory API, please join our Discord server