dora_metrics_deep_dive
Analyzes DORA metrics (Deployment Frequency, Mean Time to Recovery, Change Failure Rate) with deep correlation to code review patterns. Designed for CTOs to identify bottlenecks in software delivery pipelines. Inputs include GitHub repository identifiers and optional time ranges. Outputs structur...
This record as markdown: /tools/io-github-getgapup-gapup-mcp/dora-metrics-deep-dive.md
What dora_metrics_deep_dive does on Gapup Mcp
AI agents call dora_metrics_deep_dive to retrieve information from Gapup Mcp without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
repo | string | Yes | GitHub repository in format 'owner/repo' |
async | boolean | — | If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client ti |
since | string | — | Start date for analysis (ISO 8601) |
until | string | — | End date for analysis (ISO 8601) |
branch | string | — | Branch name to analyze (default: main) |
Parameters from the server's own tool schema.
Why dora_metrics_deep_dive is rated Low
The tool reads and analyzes existing DORA metrics and code review patterns from GitHub repositories, producing structured analytical outputs. There is no indication it modifies, executes, or deletes data. However, severity is medium because it accesses potentially sensitive engineering performance data and repository identifiers, which could expose competitive or operational intelligence if misused.
From the tool's definition Analyzes DORA metrics... Outputs structured metrics with trend analysis and code review depth insights. Inputs include GitHub repository identifiers and optional time ranges.
Attacks that exploit this kind of access
The rule that runs dora_metrics_deep_dive safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Gapup Mcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For dora_metrics_deep_dive, this is the rule to start with:
dora_metrics_deep_dive is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Gapup Mcp, apply this rule, and every dora_metrics_deep_dive call is checked against it from then on.
Questions about dora_metrics_deep_dive
Analyzes DORA metrics (Deployment Frequency, Mean Time to Recovery, Change Failure Rate) with deep correlation to code review patterns. Designed for CTOs to identify bottlenecks in software delivery pipelines. Inputs include GitHub repository identifiers and optional time ranges. Outputs structured metrics with trend analysis and code review depth insights. It is categorised as a Read tool in the Gapup Mcp MCP Server, which means it retrieves data without modifying state.
dora_metrics_deep_dive accepts 5 parameters: repo, async, since, until, branch. Required: repo. The full parameter table on this page comes from the server's own tool schema.
Register the Gapup MCP server in PolicyLayer and add a rule for dora_metrics_deep_dive: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Gapup Mcp. Nothing to install.
dora_metrics_deep_dive is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the dora_metrics_deep_dive rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for dora_metrics_deep_dive. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
dora_metrics_deep_dive is provided by the Gapup MCP server (https://mcp.gapup.io/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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