analyzing-llm-rationale: Skill for Claude Code

.agents/skills/otel-supabase-edge-style/SKILL.md

otel-supabase-edge-style is a skill for Claude Code, Codex from pareelamre/analyzing-llm-rationale. It costs 40 tokens per session (508 once invoked), scanned A, a copy of otel-supabase-edge-style, MIT.

A coding guide for adding monitoring to Supabase Edge Functions, which are small server-side functions that run on Supabase's hosted platform. It covers traces, logs, metrics, and language-model cost measurements.

In plain words
What is it for?
Use it when recording function activity, errors, timings, language-model token costs, and tenant information from Supabase Edge Functions.
Why use it?
Supabase Edge Functions cannot currently use the usual OpenTelemetry setup, so the guide describes a small compatible replacement. It also keeps the monitoring connection settings in one place.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

This is pareelamre/analyzing-llm-rationale's own configuration. It tells Claude Code and Codex how to work on analyzing-llm-rationale itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything analyzing-llm-rationale configures →

Reuse

Borrowing it

Nothing to install: this file belongs to pareelamre/analyzing-llm-rationale. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/pareelamre/analyzing-llm-rationale/main/.agents/skills/otel-supabase-edge-style/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/pareelamre/analyzing-llm-rationale

Made for: Claude Code, Codex.

Wrote 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.

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README.md
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agentmods 80×15 button for otel-supabase-edge-style

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<a href="https://agentmods.dev/skills/pareelamre/analyzing-llm-rationale/otel-supabase-edge-style"><img src="https://agentmods.dev/badge/skills/pareelamre/analyzing-llm-rationale/otel-supabase-edge-style.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 508 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00040 $0.00508
Opus 5.5 $0.00016 $0.00203
Sonnet 5.5 $0.00008 $0.00102
Haiku 4.5 $0.00004 $0.00051

Measured 2mo ago against content hash 3f5d6ea05151, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

otel-supabase-edge-style scanned grade A with 0 findings 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 2mo 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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to otel-supabase-edge-style — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agents/skills/otel-supabase-edge-style/SKILL.md · 61 lines

What it actually says

OTel Supabase Edge Style

Hosted Supabase Edge Functions do not support the normal native OTel SDK lifecycle today. Use a tiny provider-neutral shim that looks like OTel and can be deleted later if native support lands.

Good reusable API names:

tracer.startActiveSpan("edge.chat", async (span) => { ... });
span.setAttributes({ "tenant.id": tenantId });
span.setStatus({ code: SpanStatusCode.ERROR });
meter.createCounter("llm.tokens.input").add(tokens, attrs);
histogram.record(durationMs, attrs);

Bad reusable API names:

sendSuperlogSpan(...);
recordCounter(...);
trackSuperlogEvent(...);

Keep endpoint/header configuration in one setup area near the top of the function. Use the source-level public Superlog configuration pattern from otel-onboarding-style; the public project token is write-only and belongs with the endpoint in the setup block.

const SUPERLOG_ENDPOINT = "https://intake.superlog.sh";
const SUPERLOG_PUBLIC_TOKEN = "sl_public_...";

// The token MUST be sent as the `x-api-key` header. Ingest only reads
// `x-api-key` or `Authorization: Bearer <token>`; any other header name 401s.
function superlogHeaders(token: string): Record<string, string> {
  return { "x-api-key": token };
}

const OTEL_HEADERS = superlogHeaders(SUPERLOG_PUBLIC_TOKEN);

Signals

  • Traces: span around the function operation and each critical provider call.
  • Logs: concise structured OTLP log records for critical outcomes.
  • Metrics: tenant-tagged counters/histograms for critical operations.
  • LLM calls: capture llm.tokens.input / llm.tokens.output only when provider instrumentation is unavailable; tag explicit token counters with tenant, provider, model, use case, call site, and outcome. Do not calculate LLM cost in edge function code; Superlog estimates it centrally from provider/model/token data.

Use EdgeRuntime.waitUntil(...) or the runtime's equivalent when available so OTLP fetches can finish after the response is returned.

Changes

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.

  1. 2mo ago First seen · 61 lines · 40 tokens per session scan A 3f5d6ea05151

Subscribe to this mod's changes

otel-supabase-edge-style is a skill published in the GitHub repository pareelamre/analyzing-llm-rationale (0 stars, last pushed yesterday), licensed MIT. It adds 40 tokens to every session and 508 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to otel-supabase-edge-style, differing in 0 lines, and is treated as a copy.

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