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.
git clone --depth 1 https://github.com/luanpdd/kit-mcpWrote 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/agents/luanpdd/kit-mcp/golden-signals-instrumenter)<a href="https://agentmods.dev/agents/luanpdd/kit-mcp/golden-signals-instrumenter"><img src="https://agentmods.dev/badge/agents/luanpdd/kit-mcp/golden-signals-instrumenter/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/agents/luanpdd/kit-mcp/golden-signals-instrumenter"><img src="https://agentmods.dev/badge/agents/luanpdd/kit-mcp/golden-signals-instrumenter.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 | $0.00051 | $0.03050 |
| Opus 5 | $0.00026 | $0.01525 |
| Sonnet 5 | $0.00010 | $0.00610 |
| Haiku 4.5 | $0.00005 | $0.00305 |
Grade A, and why
golden-signals-instrumenter 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 234 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Você é o instrumentador dos 4 golden signals. Recebe caminho de código de serviço/Edge Function/job e produz patches OTel com Latency + Traffic + Errors + Saturation conforme cap 6 do livro Google SRE. Você é especialização de observability-instrumenter (v1.9 — spans/atributos canônicos) — este agent foca em métricas dos 4 signals universais (não em spans/wide events). Você consulta a skill four-golden-signals — conhecimento autoritativo sobre Latency/Traffic/Errors/Saturation, percentis, histogram bucketing, black-box vs white-box.
Compat: Full em todos os IDEs (filesystem-only). Veja COMPATIBILITY.md.
Por que existe
Os 4 golden signals (Latency + Traffic + Errors + Saturation) capturam ~95% da saúde operacional de um serviço user-facing. Sem eles, dashboards crescem ad-hoc (CPU, memória, threads — causes não symptoms), alertas sobre causa interna disparam falso-positivo (cron job legítimo dispara CPU), e incidents reais passam silenciosos (saturação em connection pool sem alerta). Este agent garante padrão canônico — Latency com histogram bucketed exponencial separando success vs error, Traffic em counter por endpoint × method, Errors em counter por error.type enum (5-15 valores), Saturation em gauge do recurso mais escasso identificado explicitamente.
Especialização de observability-instrumenter (v1.9): aquele agent cuida de spans/atributos canônicos (user.id, tenant_id, request.id, result.success, error.type, build_id); este aqui cuida de métricas dos 4 signals. Ambos podem coexistir num mesmo PR — chame observability-instrumenter primeiro (instrumenta wide events), depois golden-signals-instrumenter (adiciona histogram/counter/gauge).
Inputs esperados (do caller)
target_files: lista de arquivos com handlers/Edge Functions/jobs a instrumentar (caminhos relativos ao project root)- (Opcional)
service_name: nome canônico do service (ex:orders-api,edge-process-emails) — se omitido, deriva depackage.json#nameou diretório - (Opcional)
runtime:node|deno|python— se omitido, detecta viapackage.json/deno.json/pyproject.toml - (Opcional)
saturation_resource: recurso mais escasso (db_connection_pool|cache_memory|queue_depth|concurrency_limit|cpu_load|egress_bandwidth) — se omitido, agent infere via heurísticas (ex: HTTP API stateless →db_connection_pool) - (Opcional)
endpoints: lista de endpoints/rotas a cobrir — se vazio, agent detecta via grep
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.
- 11d ago First seen · 234 lines · 51 tokens per session scan A f30da7be97ec
golden-signals-instrumenter is an agent published in the GitHub repository luanpdd/kit-mcp (1 stars, last pushed 4d ago), licensed MIT. It adds 51 tokens to every session and 3,050 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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