long-running-server
Enable long-running background task support with LongRunningAgentServer. Use when: (1) Agent tasks may exceed HTTP timeout (~120s), (2) User wants background/async execution, (3) User says 'long running', 'background tasks', or 'async agent'.
65
77%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./agent-migration-from-model-serving/.claude/skills/long-running-server/SKILL.mdQuality
Discovery
89%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 solid description with excellent completeness and trigger term coverage, clearly specifying both what the skill does and when to use it with explicit numbered conditions. The main weakness is that the 'what' portion could be more specific about the concrete actions the skill enables (e.g., queuing tasks, polling status, handling timeouts) rather than just naming the general capability and component.
Suggestions
Add 2-3 specific concrete actions the skill performs, e.g., 'Configures task queuing, status polling, and result retrieval for agent tasks that exceed HTTP timeout limits.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain ('long-running background task support') and mentions a specific component ('LongRunningAgentServer'), but doesn't list multiple concrete actions—it describes a capability area rather than specific operations like 'queue tasks, poll status, retrieve results'. | 2 / 3 |
Completeness | Clearly answers both 'what' (enable long-running background task support with LongRunningAgentServer) and 'when' with explicit numbered trigger conditions including timeout scenarios, async execution needs, and specific trigger phrases. | 3 / 3 |
Trigger Term Quality | Includes natural keywords users would say: 'long running', 'background tasks', 'async agent', 'HTTP timeout', and 'background/async execution'. These cover the common variations a user might use when needing this functionality. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with a clear niche around long-running/async agent tasks and HTTP timeout handling. The specific component name 'LongRunningAgentServer' and focused trigger terms make it unlikely to conflict with other skills. | 3 / 3 |
Total | 11 / 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 well-structured, highly actionable skill with complete executable code for enabling long-running agent support. Its main weaknesses are the near-duplicate code blocks for two SDK variants that inflate the document length, and the lack of explicit validation/verification steps after completing the setup. The troubleshooting table is a nice touch that adds practical value.
Suggestions
Add an explicit verification step (e.g., 'Send a test request with background: true and confirm you can poll the result') to validate the setup works end-to-end.
Consider extracting the OpenAI SDK and LangGraph variants into separate referenced files to reduce duplication and document length.
Add a brief 'after deployment, verify by...' checkpoint before the troubleshooting section to close the feedback loop.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is fairly long (~250 lines) with two near-identical code variants (OpenAI SDK vs LangGraph) that share ~90% of their content. The table explaining request patterns and the constructor reference table add value, but the duplicated code blocks and some explanatory comments could be tightened significantly. | 2 / 3 |
Actionability | The skill provides fully executable, copy-paste-ready code for every step — complete Python files, YAML config snippets, .env examples, and utility functions. Each step has concrete, specific guidance with real import paths and parameter values. | 3 / 3 |
Workflow Clarity | The 7-step sequence is clearly numbered and logically ordered, but there are no explicit validation checkpoints or feedback loops. After making all these changes, there's no 'verify it works' step — Step 7 just defers to another skill. For a multi-step process involving database configuration and server changes, missing verification caps this at 2. | 2 / 3 |
Progressive Disclosure | The skill appropriately references the lakebase-setup skill for prerequisite and deployment steps, avoiding duplication. However, the two SDK variants (OpenAI vs LangGraph) are fully inlined, making the document very long. These could be split into separate referenced files. No bundle files are provided to support progressive disclosure. | 2 / 3 |
Total | 9 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- databricks/app-templates
- Commit
1c88215
- Reviewed
Table of Contents
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