Get project progress
project_progressReturn the issue counts for a project, in total and per milestone, so you can report how far along it is.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| project | Yes | Project name, slug or id. |
project_progressReturn the issue counts for a project, in total and per milestone, so you can report how far along it is.
| Name | Required | Description | Default |
|---|---|---|---|
| project | Yes | Project name, slug or id. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds that it returns counts (total and per milestone), which is behavioral information beyond the annotations. It doesn't add details about permissions or edge cases, but for a simple read operation this is adequate. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, well-structured sentence that immediately states the action and the return value. No filler, and the key information (total and per milestone) is front-loaded. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with one well-documented parameter and no output schema, the description fully explains what the tool returns (issue counts total and per milestone). An agent can call it correctly and know what to expect from the response without needing additional details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of parameters with a clear description ('Project name, slug or id.'). The tool description does not add anything further about the parameter, which is fine because the schema is complete. Baseline 3 is appropriate since the description doesn't need to compensate for any coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Return' with the resource 'issue counts for a project, in total and per milestone'. This clearly distinguishes it from sibling tools like list_projects (which lists projects) and cycle_progress (which presumably focuses on cycles). It states exactly what data the agent will receive.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the use case: 'so you can report how far along it is'. It doesn't explicitly mention alternatives or when not to use it, but the purpose is clear enough that an agent would know to call this when needing progress metrics rather than a list of projects or milestones. It lacks explicit exclusions but gives sufficient context.
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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