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knowl_task_checkpoint

Record manual task progress and blockers using a task ID, keeping completed steps, next actions, and verification status resumable across AI agent sessions.

Instructions

Checkpoint meaningful progress or a blocker in a manual work loop using the taskId from knowl_task_start. Never use for a hook-owned session or routine command noise.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalNoOptional current goal for resumable handoffs.
taskIdYesThe taskId returned by knowl_task_start.
blockerNoOptional current blocker.
summaryYesDurable checkpoint summary.
completedNoOptional list of completed steps.
nextActionNoOptional next action to resume with.
artifactRefsNoOptional file or artifact references relevant to the task.
verificationStatusNoOptional verification status such as unverified, tests-passing, or needs-review.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv5.23.0

TDQS

A3.5/5.0
Behavior2/5

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

Annotations only say openWorldHint=false and destructiveHint=false, so the description carries most behavioral burden. It states the action is a 'checkpoint' but does not disclose that this persists a snapshot for later resume, whether it can overwrite prior checkpoints, or that it does not finish the task. This is a significant gap for a state-mutating tool in a manual work loop.

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?

Two sentences with no filler; the first sentence states the action and scope, and the second sentence adds a sharp exclusion. Every word earns its place, and the restriction is front-loaded rather than buried.

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

Completeness3/5

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

For a tool with 8 parameters, no output schema, and sparse annotations, the description gives the essential usage context but leaves lifecycle details (relationship to knowl_task_finish/knowl_resume, what happens on repeated checkpoints, response shape) to be inferred from the schema and sibling names. Adequate but not fully complete.

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 coverage is 100%, so all eight parameters already have meaningful descriptions. The tool description adds that taskId comes from knowl_task_start and frames summary as progress/blocker, which is helpful but not extensive. Baseline 3 fits because the schema does the heavy lifting.

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

Purpose4/5

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

The description identifies a specific action ('Checkpoint meaningful progress or a blocker') on a task resource scoped to a 'manual work loop' and explicitly ties it to the taskId from knowl_task_start. It does not explicitly contrast with knowl_task_finish, but the 'progress or blocker' framing prevents confusion with task completion.

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

Usage Guidelines4/5

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

It explicitly states when to use the tool (manual work loop) and when not to use it ('Never use for a hook-owned session or routine command noise'). It does not name an alternative tool, so it stops short of the full five-level criterion, but the exclusions are clear and actionable.

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