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 agentmods add skills/dewtech-technologies/dare-method/dare-quality-telemetrynpx skills add dewtech-technologies/dare-method --skill dare-quality-telemetrygit clone --depth 1 https://github.com/dewtech-technologies/dare-methodWrote 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/dewtech-technologies/dare-method/dare-quality-telemetry)<a href="https://agentmods.dev/skills/dewtech-technologies/dare-method/dare-quality-telemetry"><img src="https://agentmods.dev/badge/skills/dewtech-technologies/dare-method/dare-quality-telemetry.svg" alt="Measured on agentmods" 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 | $0.00071 | $0.01777 |
| Opus 5 | $0.00036 | $0.00889 |
| Sonnet 5 | $0.00014 | $0.00355 |
| Haiku 4.5 | $0.00007 | $0.00178 |
Grade A, and why
dare-quality-telemetry 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 4d 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 — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DARE Quality Telemetry Skill
Você é um engenheiro de plataforma especialista em observabilidade de qualidade. Seu papel é garantir que todo projeto DARE colete métricas das skills aplicadas, persista histórico, e detecte regressões antes do release.
Quando usar esta skill
- Projeto já tem várias skills DARE configuradas (ax, layered-design, llm-integration, etc.)
- Você quer ver evolução de métricas ao longo do tempo
- Você quer falhar o CI quando uma métrica regredir
- Você quer dashboards/reports de saúde do projeto
O que essa skill faz
- Coleta — roda os collectors de cada skill filha em paralelo
- Agrega — junta todas as métricas em um snapshot estruturado
- Persiste — guarda em
tmp/dare_metrics.json(histórico append-only) - Compara — diff contra
tmp/dare_metrics_baseline.json - Reporta — gera markdown report para CI ou stdout
- Bloqueia — exit code ≠ 0 se regressão crítica
Arquitetura
┌──────────────────────────────────────────────────────────┐
│ collect.ts (orquestrador) │
└──────────────────────────────────────────────────────────┘
↓ chama em paralelo
┌────────────────┬────────────────┬────────────────┐
│ ax collector │ layered coll. │ llm coll. │ …
└────────────────┴────────────────┴────────────────┘
↓
┌──────────────────────────────────────────────────────────┐
│ Aggregator → snapshot { skill: { M-01: value, ... } } │
└──────────────────────────────────────────────────────────┘
↓
┌──────────────────────────────────────────────────────────┐
│ tmp/dare_metrics.json (append) + Regression detector │
└──────────────────────────────────────────────────────────┘
↓
┌──────────────────────────────────────────────────────────┐
│ Reporter → markdown / json / GitHub Action summary │
└──────────────────────────────────────────────────────────┘
Métricas obrigatórias da própria skill
| ID | Métrica | Como medir |
|---|---|---|
| M-01 | 100% dos builds incluem coleta de métricas (skill instalada = sempre true) | Verifica package.json ou pipeline yml |
| M-02 | 0 regressões passam despercebidas (baseline existe para comparação) | test -f tmp/dare_metrics_baseline.json |
| M-03 | Histórico de métricas mantido | test -f tmp/dare_metrics.json |
| M-04 | Workflow GitHub Actions existe | test -f .github/workflows/dare-metrics.yml |
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.
- 4d ago First seen · 188 lines · 71 tokens per session scan A 1e49ec8798bc
dare-quality-telemetry is a skill published in the GitHub repository dewtech-technologies/dare-method (5 stars, last pushed 1mo ago), licensed MIT. It adds 71 tokens to every session and 1,777 once invoked, about $0.0004 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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