get_skill_instructions
Return the full AI Readiness skill workflow (research, classification, file generation)
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
AI Readiness Kit
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- First observed
TDQS
A3.5/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states 'Return' implying a read operation, but does not mention permissions, side effects, or limitations. For a retrieval tool, basic safety information is missing.
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 with no wasted words. It is front-loaded with the main action and details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and no output schema, the description could be considered adequate but minimal. It lists the workflow components but does not explain what each entails, which may leave an agent uncertain about the content.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so baseline is 4. The description does not need to explain parameters, and it adds value by describing the tool's output.
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 returns the full AI Readiness skill workflow, listing the three components (research, classification, file generation). It uses a specific verb+resource and distinguishes from sibling tools like generate_ai_readiness_files which focuses on generation.
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?
No explicit guidance on when to use this tool versus alternatives such as generate_ai_readiness_files or get_file_spec. The description does not provide context for selection.
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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TDQS
A3.7/5.0
Disambiguation5/5
Each tool targets a distinct purpose: generating the full workflow, converting a specific file, retrieving specs, classification guide, instructions, or listing files. No overlapping functionality.
Naming Consistency5/5
All tools use consistent snake_case with verb_noun structure (generate_*, get_*, list_*), making the set predictable and easy to navigate.
Tool Count5/5
With 6 tools, the set covers the core informational needs (specs, guide, instructions, file list) plus the main workflow generator and a format converter, which is well-scoped for the domain.
Completeness2/5
The tool set lacks tools for actually writing or outputting the generated files; 'generate_ai_readiness_files' returns a workflow but no file creation tool exists, leaving a significant gap in the lifecycle.