gha-intel-mcp

Analyze Workflow Config

analyze_workflow_config

Analyze GitHub Actions workflow YAML to identify optimization opportunities: missing caches, matrix strategy, concurrency controls, slow dependency installs, and artifact handling.

Instructions

Parse a GitHub Actions workflow YAML (provided as a string) and identify optimization opportunities: missing caches, matrix strategy, concurrency controls, slow dependency installs, artifact handling, and more.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "workflow_content": "<workflow_content>"
    },
    "name": "analyze_workflow_config"
  }
}

Input Schema

Name	Required	Description	Default
`workflow_content`	Yes	Full YAML content of the GitHub Actions workflow file

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.4.3Aug 20, 2026

TDQS

A3.8/5.0

Behavior3/5

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

No annotations are provided, so the description carries the burden of disclosure. It says the tool 'parses' and 'identifies' optimization opportunities, implying read-only analysis. However, it doesn't state whether it modifies anything, whether it requires valid YAML, or what happens on invalid input. The description doesn't contradict annotations, but it adds minimal behavioral detail beyond the action itself.

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 sentence that packs substantial information: the input format (YAML string), the action (parse and identify optimization opportunities), and specific examples of what it looks for. Every element earns its place, and it's front-loaded with the core purpose.

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?

Given it's a single-parameter tool with a descriptive schema, no output schema, and no annotations, the description covers the essential aspects: input format, purpose, and analysis areas. It's quite complete for its simplicity. The only gap is specifying expected output format, but since no output schema exists, the description should ideally mention what the analysis returns, though it's not critical for invocation.

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 single parameter 'workflow_content' has a clear schema description 'Full YAML content of the GitHub Actions workflow file', and schema coverage is 100%. The description adds the context of what the tool does with it (parse and analyze) but doesn't add format expectations beyond what the schema says. Baseline 3 is appropriate.

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 parses a GitHub Actions workflow YAML string and identifies optimization opportunities, listing specific areas (caches, matrix strategy, concurrency, dependency installs, artifacts). This is a specific verb 'analyze' with a clear resource 'workflow config' and distinct purpose from siblings like list_workflow_performance and get_billing_usage, which focus on performance listing and billing.

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

Usage Guidelines3/5

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

The description implies when to use: when you have a workflow YAML string to analyze for optimization. It does not explicitly contrast with siblings or mention when not to use. While the purpose is clear, there is no explicit guidance on alternatives or exclusions, so it's adequate but lacks depth.

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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