AD neon-functions
Long-running, serverless Node.js HTTP functions deployed onto your Neon branch, with DATABASE_URL injected automatically and compute that runs next to your data. Use when a user wants to host an API, an AI agent with long streaming responses, a WebSocket or server-sent-events (SSE) server, a webhook handler, a Discord bot, an MCP server, or any request/response workload that risks timing out on short, lambda-style serverless functions — and wants it to branch with their database. Triggers include "serverless function", "deploy an API", "long-running function", "streaming agent", "SSE server", "WebSocket server", "webhook handler", "MCP server", "run code next to my database", "function that won't time out", "Neon Functions", and "Neon Compute".
Long-running, serverless Node.js HTTP functions deployed onto your Neon branch, with DATABASEURL injected automatically and compute that runs next to your…
As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 9159 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 43/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 49 mutating operations with no state check
- 40Execution cost. Instruction body is 9159 tokens: crowds the task out of the window
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash, web, node) that frontmatter does not declare
- 85Steps. 34 steps, 3 vague phrases
- 100Consistency. Name and required fields are in place
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 17 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (5 tags): a typed call is more reliable
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -2localhost URLs: will not work for another user
- +1No license
- +2Single-language instructions
- +5Description quotes 12 example trigger phrases
- +3Description length 754: enough signal without eating the budget
- +4Structure: 21 headings
- +3Step-by-step instructions: 34 items
- +4Has examples (20 code blocks)
- +4Reference files are cited in the instructions (6 of 6)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.