DeepMark

Get Mark Result by Answer ID

markResult_get

Read-onlyIdempotent

Retrieve the marking result for a specific answer by its ID

Input Schema

TableJSON Schema

Name	Required	Description	Default
`answer_id`	Yes	The unique identifier for the answer to retrieve the marking result for

Output Schema

TableJSON Schema

Name	Required	Description
`answer_id`	Yes
`marked_at`	Yes	ISO-8601 timestamp the mark was recorded.
`mark_points`	Yes	Per-mark-point decisions (point_based questions); [] otherwise.
`mark_scheme`	Yes
`total_score`	Yes
`llm_reasoning`	Yes
`feedback_summary`	Yes
`max_possible_score`	Yes

Schema Changelog

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

First observedJul 22, 2026

TDQS

A3.5/5.0

Behavior2/5

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

Annotations already declare readOnlyHint and idempotentHint, so the safety profile is known. The description adds no extra behavioral traits such as error handling for missing IDs or side effects, providing no value beyond the annotations.

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, concise sentence with no redundant words. It is front-loaded with the action and resource, making it easy to parse.

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?

For a simple read-only lookup with one parameter, an output schema, and good annotations, the description is fully adequate. It clearly states the purpose, and the output schema covers return values, so nothing essential is missing.

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% with a clearly described answer_id parameter, so the schema fully documents the parameter. The description does not add additional meaning or context for the parameter, earning the baseline score 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 the tool retrieves a marking result for a specific answer by ID, using the verb 'Retrieve' and identifying the resource. It distinguishes itself from sibling get tools like submission_get and paper_get by specifying 'marking result'.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives, nor does it mention exclusions or complementary tools. The sibling list contains other getters, but no differentiation is given.

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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TDQS

A4/5.0

Disambiguation4/5

The tools map well to distinct resources and workflow stages, and the async flows are clearly explained. The main overlap risk is paper_create/paper_confirm and markResult_get/submission_get, where names point at similar actions but the descriptions make the boundaries usable.

Naming Consistency4/5

Most names follow the same resource_action snake_case pattern, e.g. paper_get, submission_mark, markScheme_update. markResult_get breaks the pattern slightly by mixing camelCase into an otherwise snake_case set, but the naming stays readable and predictable overall.

Tool Count5/5

Ten tools is a well-scoped size for this domain: paper creation, confirmation, retrieval, question/mark-scheme correction, and submission grading are covered without excess granularity or obvious filler.

Completeness4/5

The main end-to-end workflow—create extraction job, confirm paper, mark submission, poll results—is complete and coherent. Minor gaps exist, such as no paper deletion, no submission listing, and no direct way to fetch a mark scheme separately, but they are not blocking for the core grading loop.

Resources

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