Skip to main content
Glama

analyze_peer_review_quality

Read-only

Analyze peer review quality by evaluating comments against criteria and generating a detailed report.

Instructions

Analyze the quality and content of peer review comments.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
assignment_idYesCanvas assignment ID
generate_reportNoGenerate detailed analysis report
analysis_criteriaNoJSON string of custom criteria
course_identifierYesCourse code or Canvas ID
Behavior3/5

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

The readOnlyHint annotation already covers safety, and the description's 'Analyze' wording is consistent with a read-only operation. The description adds the scope of analysis ('quality and content') but does not disclose report generation behavior, output format, or any other execution traits beyond the schema.

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 a single front-loaded sentence with no redundant or filler content. It is concise, though slightly terse given the tool's four parameters and the absence of an output schema.

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?

The tool has no output schema and sits among many closely related peer-review tools, but the description does not explain what the analysis returns, how generate_report affects behavior, or how analysis_criteria customizes results. This leaves significant gaps for an agent deciding how to invoke and interpret the tool correctly.

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 description coverage is 100%, so all four parameters are already documented. The description adds no semantic detail about course_identifier, assignment_id, analysis_criteria, or generate_report, so it does not exceed the baseline established by the schema.

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 uses a specific verb ('Analyze') and resource ('peer review comments') to convey a clear read-only analysis action, including the dual object of 'quality and content.' However, it does not differentiate from overlapping siblings like get_peer_review_comments or identify_problematic_peer_reviews, which likely analyze similar data.

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?

There is no guidance about when to use this tool versus alternatives such as generate_peer_review_report, identify_problematic_peer_reviews, or get_peer_review_comments. The description states only what the tool does, not when it should be preferred or excluded.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/vishalsachdev/canvas-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server