Build container-based Foundry Agents with Azure AI Projects SDK (ImageBasedHostedAgentDefinition). Use when creating hosted agents with custom container images in Azure AI Foundry.
55
62%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/antigravity-awesome-skills-claude/skills/agents-v2-py/SKILL.mdQuality
Discovery
75%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
The description is well-structured with a clear 'Use when' clause and targets a very specific niche (container-based Azure AI Foundry agents), making it distinctive and complete. Its main weakness is that it only names one action ('build') rather than listing multiple concrete capabilities, and the trigger terms are heavily technical without covering common user phrasings.
Suggestions
Add more specific actions beyond 'build', such as 'configure container settings, set environment variables, deploy and manage hosted agents'.
Include additional natural trigger terms users might use, such as 'Docker image', 'containerized agent', 'deploy agent', or 'agent hosting'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (container-based Foundry Agents) and a key action (build), and mentions a specific SDK class (ImageBasedHostedAgentDefinition), but only describes one action rather than listing multiple concrete capabilities like configuration, deployment, or debugging. | 2 / 3 |
Completeness | Clearly answers both 'what' (build container-based Foundry Agents with Azure AI Projects SDK using ImageBasedHostedAgentDefinition) and 'when' (Use when creating hosted agents with custom container images in Azure AI Foundry), with an explicit 'Use when' clause. | 3 / 3 |
Trigger Term Quality | Includes relevant technical terms like 'container', 'Foundry Agents', 'Azure AI Projects SDK', 'custom container images', and 'Azure AI Foundry', but these are fairly specialized. Missing common variations users might say like 'Docker', 'deploy agent', 'hosted container', or 'agent deployment'. | 2 / 3 |
Distinctiveness Conflict Risk | Highly specific niche targeting container-based hosted agents in Azure AI Foundry with a named SDK class (ImageBasedHostedAgentDefinition). Very unlikely to conflict with other skills due to the precise technology stack and pattern specified. | 3 / 3 |
Total | 10 / 12 Passed |
Implementation
50%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill is highly actionable with concrete, executable code examples covering sync/async patterns, multiple tool configurations, and a useful error reference table. However, it suffers from significant redundancy — the authentication, core workflow, and complete example sections largely duplicate each other. The workflow lacks validation checkpoints (e.g., checking deployment state after creation) and the monolithic structure would benefit from splitting detailed reference content into separate files.
Suggestions
Eliminate redundant sections: merge Authentication into Core Workflow, remove the Complete Example (or make it the only full example and trim earlier sections to fragments), and consolidate the Resource Allocation / Protocol Versions / Tools sections into the parameter table with brief inline examples.
Add validation checkpoints to the workflow: after create_version, show how to check agent.state for successful deployment, and include a polling/retry pattern for common transient failures like ImagePullBackOff.
Split the parameter reference table, tools configuration details, and common errors into a separate REFERENCE.md file, keeping SKILL.md as a concise quick-start with pointers to the reference.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Significant verbosity and redundancy throughout. The Authentication section repeats code shown in the Core Workflow. The Complete Example is essentially a copy of the Core Workflow section. Resource Allocation, Protocol Versions, and Tools Configuration sections repeat patterns already shown. The parameter table, while useful, is followed by sections that re-explain each parameter with near-identical code snippets. Much content could be cut by 50%+ without losing information. | 1 / 3 |
Actionability | The skill provides fully executable, copy-paste ready Python code with correct imports, concrete parameter values, and specific examples for sync and async patterns. The parameter table, error table, and tool configuration examples are all concrete and specific. | 3 / 3 |
Workflow Clarity | The core workflow is clearly sequenced (imports → create → list → delete), but there are no validation checkpoints. There's no guidance on verifying the agent actually deployed successfully (e.g., checking agent.state, polling for readiness), no error handling in the workflow steps, and no feedback loop for common failures like ImagePullBackOff despite listing them in the errors table. | 2 / 3 |
Progressive Disclosure | The content is organized with headers and sections, but it's monolithic — everything is inline in a single long file with no content split into supporting files. The reference links at the bottom point to external docs but there are no bundle files for advanced topics like ACR setup, capability host configuration, or detailed troubleshooting that could be separated out. For a skill this long (~200+ lines), splitting would improve navigation. | 2 / 3 |
Total | 8 / 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 | |
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Table of Contents
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