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checkpoint_record

Record or update a checkpoint with supporting evidence to mark progress and validate healthy completion. Track status across targets, linking proof and state for reliable task closure.

Instructions

Create or update a checkpoint with evidence. Passed checkpoints are the only basis for healthy completion states.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNo
actorNo
titleYes
planIdNo
statusYes
gitHeadNo
coverageNo
criteriaNo
evidenceNo
targetIdYes
targetTypeYes
projectRootNo
chainScopeIdNo
evidenceLevelNo
invalidatedAtNo
checkpointKindNo
expectedRevisionNo
aggregationPolicyNo
includeStructuredNo
eligibleAfterChildrenNo
requiredEvidenceLevelNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does reveal that the tool mutates state by creating or updating a checkpoint and that passed checkpoints are central to completion health, but it omits upsert semantics, invalidation behavior, revision handling, evidence validation, and side effects on related checkpoints. This is under-disclosed for a mutation tool.

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

Conciseness4/5

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

The description is concise: two short sentences, with the operative verb front-loaded and no filler. It is efficient and easy to parse, though a structured breakdown of key behaviors would have been more helpful for a tool of this complexity.

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

Completeness2/5

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

For a 21-parameter mutation tool with 4 required fields, no annotations, and no output schema, this description is far too thin. It leaves out core operational details such as how targets are identified, what status transitions are allowed, how evidence should be structured, and what the tool returns or changes after invocation.

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

Parameters2/5

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

Schema description coverage is 0%, and the description adds very little parameter-level meaning. It hints that 'evidence' is relevant and that 'passed' status is significant, but it does not explain the required targetType/targetId/title/status combination or any of the many optional fields. An agent would have to infer nearly all parameter semantics from property names and enums alone.

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 states a clear verb-resource pair: 'Create or update a checkpoint' with a meaningful qualifier, 'with evidence.' It also adds domain significance by saying passed checkpoints are the basis for healthy completion states, which helps distinguish this from read-only siblings like checkpoint_list. It is not tautological and is clear enough for an agent to know what the tool does.

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 this tool matters, especially for recording passed checkpoints, but it never explicitly says when to use this versus alternatives such as checkpoint_list or graph_mutate. There are no stated exclusions, prerequisites, or guidance about when not to use it, so usage context is only implied.

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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