Skip to main content
Glama

Update Question by ID

question_update
Idempotent

Update an existing GCSE question by its ID

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe unique identifier for the question to update
topicNoThe topic or subject matter for the question
pointsNoNumber of marks the question is worth
subjectNoSubject area for the question
question_textNoThe exam question
difficulty_levelNoDifficulty level of the question

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYes
pointsYes
subjectYes
updatedYesNames of the fields written by this call.
question_idYes
difficulty_levelYes

Schema Changelog

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

  1. First observed

TDQS

A3.8/5.0
Behavior2/5

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

The annotations already provide safety information (readOnlyHint=false, destructiveHint=false, idempotentHint=true). The description adds no additional behavioral context, such as whether the update is partial or how missing fields are handled, providing minimal value beyond the structured 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, direct sentence that immediately conveys the verb, resource, and identifier without any superfluous words. It is perfectly concise and well-structured.

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?

The tool is well-supported by a complete schema, meaningful annotations, and an existing output schema. The description, while brief, is sufficient for an agent to understand the tool's purpose and invoke it correctly. There is a minor gap in explicit usage guidance, but overall completeness is high.

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?

The schema fully describes all six parameters with individual descriptions, and the description does not add parameter-specific information beyond mentioning the ID. With 100% schema coverage, the baseline score of 3 applies.

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's function: 'Update an existing GCSE question by its ID.' It uses a specific verb ('update') and resource ('GCSE question'), and identifies the required identifier ('by its ID'), distinguishing it from sibling tools like markScheme_update or paper_confirm.

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?

The description implies the tool is for modifying an existing question, which is a clear context. However, it does not explicitly mention alternatives or exclusions. Since no sibling tool updates questions, the context is sufficient, but it lacks explicit guidance on when not to use it.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

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