Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add build-with-dhiraj/ai-workflow-framework-portability-kit --skill observabilitygit clone --depth 1 https://github.com/build-with-dhiraj/ai-workflow-framework-portability-kitWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/build-with-dhiraj/ai-workflow-framework-portability-kit/observability)<a href="https://agentmods.dev/skills/build-with-dhiraj/ai-workflow-framework-portability-kit/observability"><img src="https://agentmods.dev/badge/skills/build-with-dhiraj/ai-workflow-framework-portability-kit/observability/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/build-with-dhiraj/ai-workflow-framework-portability-kit/observability"><img src="https://agentmods.dev/badge/skills/build-with-dhiraj/ai-workflow-framework-portability-kit/observability.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00063 | $0.07362 |
| Opus 5.5 | $0.00025 | $0.02945 |
| Sonnet 5.5 | $0.00013 | $0.01472 |
| Haiku 4.5 | $0.00006 | $0.00736 |
Grade A, and why
observability scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -N -H "Authorization: Bearer $VERCEL_TOKEN" \ How it starts
The opening of the file, as written. The whole thing — 814 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Vercel Observability
You are an expert in Vercel's observability stack — runtime logs, structured logging, Drains, Web Analytics, Speed Insights, and monitoring integrations. Always start with logging. When something is stuck, slow, or broken, the first step is always to check or add logs.
Structured Logging Baseline
Add this to every API route and server action as a minimum. If the user reports something stuck, hanging, or slow, verify this baseline exists first:
const start = Date.now();
console.log(JSON.stringify({ level: "info", msg: "start", route: "/api/example", requestId: req.headers.get("x-vercel-id") }));
// ... your logic ...
console.log(JSON.stringify({ level: "info", msg: "done", route: "/api/example", ms: Date.now() - start }));
// On error:
console.error(JSON.stringify({ level: "error", msg: "failed", route: "/api/example", error: err.message, ms: Date.now() - start }));
Runtime Logs
Vercel provides real-time logs for all function invocations.
Structured Logging
// app/api/process/route.ts
export async function POST(req: Request) {
const start = Date.now()
const data = await req.json()
// Structured logs appear in Vercel's log viewer
console.log(JSON.stringify({
level: 'info',
message: 'Processing request',
requestId: req.headers.get('x-vercel-id'),
payload_size: JSON.stringify(data).length,
}))
try {
const result = await processData(data)
console.log(JSON.stringify({
level: 'info',
message: 'Request completed',
duration_ms: Date.now() - start,
}))
return Response.json(result)
} catch (error) {
console.error(JSON.stringify({
level: 'error',
message: 'Processing failed',
error: error instanceof Error ? error.message : String(error),
duration_ms: Date.now() - start,
}))
return Response.json({ error: 'Internal error' }, { status: 500 })
}
}
Next.js Instrumentation
// instrumentation.ts (Next.js 16)
export async function register() {
if (process.env.NEXT_RUNTIME === 'nodejs') {
// Initialize monitoring on server startup
const { initMonitoring } = await import('./lib/monitoring')
initMonitoring()
}
}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 814 lines · 63 tokens per session scan A 93307ecb076e
observability is a skill published in the GitHub repository build-with-dhiraj/ai-workflow-framework-portability-kit (5 stars, last pushed 20d ago), licensed MIT. It adds 63 tokens to every session and 7,362 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-21.
Other skills, from other repositories
semgrep-rule-creator
Creates custom Semgrep rules for detecting security vulnerabilities, bug patterns, and code patterns. Use when writing Semgrep rules or building custom static analysis detections.
variant-analysis
Find similar vulnerabilities and bugs across codebases using pattern-based analysis. Use when hunting bug variants, building CodeQL/Semgrep queries, analyzing security vulnerabilities, or performing systematic code audits after finding an initial issue.
fp-check
Systematically verifies suspected security bugs to eliminate false positives. Produces TRUE POSITIVE or FALSE POSITIVE verdicts with documented evidence for each bug.
vuln-report
Turn one confirmed security finding into a disclosure-ready GitHub advisory with root cause, proof of concept, impact, and source evidence. Use for reporting an established vulnerability, not discovering or validating one.
huggingface-spaces
Build, deploy, debug, or maintain a Hugging Face Space using Gradio, Docker, or Static SDKs. Use for general Space hosting and configuration; use huggingface-zerogpu for ZeroGPU runtime constraints and lora-space-builder for LoRA demos.
huggingface-zerogpu
Implement or debug Hugging Face Spaces ZeroGPU code using @spaces.GPU, including isolation, state, duration, sizing, and CUDA-wheel constraints. Use for ZeroGPU-specific behavior; use huggingface-spaces for general hosting.