lambda
AWS Lambda serverless functions for event-driven compute. Use when creating functions, configuring triggers, debugging invocations, optimizing cold starts, setting up event source mappings, or managing layers.
87
82%
Does it follow best practices?
Impact
96%
1.10xAverage score across 3 eval scenarios
Passed
No known issues
Quality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a well-crafted skill description that excels across all dimensions. It provides specific capabilities, uses natural AWS Lambda terminology, includes an explicit 'Use when...' clause with multiple trigger scenarios, and is distinctive enough to avoid conflicts with other cloud or serverless skills.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'creating functions, configuring triggers, debugging invocations, optimizing cold starts, setting up event source mappings, managing layers' - these are all distinct, actionable capabilities. | 3 / 3 |
Completeness | Clearly answers both what ('AWS Lambda serverless functions for event-driven compute') and when with explicit 'Use when...' clause listing six specific trigger scenarios. | 3 / 3 |
Trigger Term Quality | Includes natural keywords users would say: 'Lambda', 'serverless', 'functions', 'triggers', 'cold starts', 'event source mappings', 'layers' - good coverage of AWS Lambda terminology that users would naturally mention. | 3 / 3 |
Distinctiveness Conflict Risk | Highly specific to AWS Lambda with distinct triggers like 'cold starts', 'event source mappings', and 'layers' that are unique to Lambda; unlikely to conflict with general cloud or function skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a solid, actionable AWS Lambda skill with excellent executable code examples in both CLI and Python. The main weaknesses are verbosity in the concepts section (explaining things Claude knows), lack of validation checkpoints in workflows, and a monolithic structure that could benefit from splitting detailed reference content into separate files.
Suggestions
Remove or significantly trim the Core Concepts section - Claude knows what Lambda functions, cold starts, and layers are; focus only on project-specific conventions or non-obvious details
Add explicit validation steps to workflows, e.g., after create-function: 'Verify: aws lambda get-function --function-name MyFunction' and check for expected state
Split CLI Reference and Troubleshooting sections into separate files (CLI_REFERENCE.md, TROUBLESHOOTING.md) and link from the main skill
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is generally efficient but includes some unnecessary explanations Claude would know (e.g., 'Lambda runs code without provisioning servers', basic concept definitions). The core concepts section could be trimmed significantly. | 2 / 3 |
Actionability | Excellent executable code examples throughout - both AWS CLI and boto3 with complete, copy-paste ready commands. Specific parameters, ARN formats, and real configuration values are provided. | 3 / 3 |
Workflow Clarity | Individual operations are clear but multi-step workflows lack explicit validation checkpoints. For example, creating a function doesn't include verification steps, and the troubleshooting section provides fixes but no feedback loops for confirming resolution. | 2 / 3 |
Progressive Disclosure | Has a table of contents and organized sections, but the document is monolithic at ~300 lines. CLI reference tables and detailed troubleshooting could be split into separate files. References to external docs are present but internal progressive disclosure is missing. | 2 / 3 |
Total | 9 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- itsmostafa/aws-agent-skills
- Commit
5df6da7
- Reviewed
Table of Contents
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.