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kagan-sh

Kagan - AI Orchestration Layer

checkpoint_list

List all checkpoints for a task's current session, sorted by step index, to monitor task progress.

Instructions

List all checkpoints for the task's current session.

Returns checkpoints sorted by step_index (ascending). task_id is the ID of the task to query.

Returns dict with: task_id, session_id, checkpoints (list of checkpoint dicts).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
task_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Since no annotations are provided, the description carries the full burden of disclosing behavioral traits. It explains the sorting order (by step_index ascending) and the return structure (dict with task_id, session_id, checkpoints), which is beyond the schema. However, it does not mention error handling or rate limits, which are minor for a simple list tool.

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 concise, with the first sentence stating the primary purpose, followed by sorting, parameter explanation, and return format. Every sentence adds value, and there is no redundancy. The structure is front-loaded and efficient.

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

Completeness5/5

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

Given the tool's simplicity (one required parameter, no annotations, output schema exists), the description is complete. It covers the purpose, sorting, parameter meaning, and return structure. There is no missing information that would hinder an agent from using the tool correctly.

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

Parameters4/5

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

The input schema only defines task_id as a string with no description. The tool description adds meaning by explaining that task_id is 'the ID of the task to query', which provides context beyond the schema. With 0% schema description coverage, this compensation is valuable.

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 the action ('List all checkpoints'), the resource ('checkpoints'), and the scope ('for the task's current session'). It also specifies sorting by step_index, which differentiates it from the sibling 'checkpoint_create' tool, which creates checkpoints.

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

Usage Guidelines3/5

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

The description implies when to use this tool (to list checkpoints) but does not explicitly state when not to use it or provide alternatives. The context with sibling 'checkpoint_create' suggests the distinction, but there is no direct guidance on usage scenarios.

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

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