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/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/commands/dewtech-technologies/dare-method/dare-quality-telemetry)<a href="https://agentmods.dev/commands/dewtech-technologies/dare-method/dare-quality-telemetry"><img src="https://agentmods.dev/badge/commands/dewtech-technologies/dare-method/dare-quality-telemetry/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/commands/dewtech-technologies/dare-method/dare-quality-telemetry"><img src="https://agentmods.dev/badge/commands/dewtech-technologies/dare-method/dare-quality-telemetry.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 | $0.00000 | $0.01156 |
| Opus 5.5 | $0.00000 | $0.00462 |
| Sonnet 5.5 | $0.00000 | $0.00231 |
| Haiku 4.5 | $0.00000 | $0.00116 |
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 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.
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 — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/dare-quality-telemetry
Coleta métricas das skills DARE (ax, layered-design, llm-integration, frontend, realtime…), persiste histórico em tmp/dare_metrics.json e detecta regressões contra baseline.
Como usar
/dare-quality-telemetry collect # roda todos os collectors
/dare-quality-telemetry baseline # captura baseline atual
/dare-quality-telemetry compare # compara contra baseline (CI)
/dare-quality-telemetry report # gera markdown report
O que faz
- Roda collectors das skills configuradas em paralelo
- Agrega em um snapshot
- Persiste em
tmp/dare_metrics.json - Compara com
tmp/dare_metrics_baseline.json - Reporta em markdown / JSON
- Exit code ≠ 0 se regressão crítica
Arquitetura
collect.ts
↓ chama em paralelo
[ax collector] [layered coll.] [llm coll.] [frontend coll.] [realtime coll.]
↓
Aggregator → snapshot { skill: { M-01: value, ... } }
↓
tmp/dare_metrics.json + Regression detector
↓
Reporter → markdown / JSON / GH Actions summary
Métricas obrigatórias
| ID | Métrica |
|---|---|
| M-01 | 100% dos builds incluem coleta (skill instalada = true) |
| M-02 | 0 regressões passam despercebidas (baseline existe) |
| M-03 | Histórico mantido em tmp/dare_metrics.json |
| M-04 | Workflow .github/workflows/dare-metrics.yml existe |
Configuração
# dare.config.yml
telemetry:
skills:
- dare-ax
- dare-layered-design
- dare-llm-integration
- dare-frontend-design
- dare-realtime
output: tmp/dare_metrics.json
baseline: tmp/dare_metrics_baseline.json
fail_on_regression: true
Schema do snapshot
{
"timestamp": "2026-05-26T10:30:00Z",
"commit": "1d4a1417",
"branch": "main",
"skills": {
"dare-ax": {
"M-01": { "value": 1.0, "status": "PASS" },
"M-04": { "value": 1.0, "status": "PASS" }
},
"dare-layered-design": {
"M-01": { "value": 0.95, "status": "PASS" }
}
}
}
Detecção de regressão
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 · 167 lines · 0 tokens per session scan A 1e422386d2d5
dare-quality-telemetry is a command published in the GitHub repository dewtech-technologies/dare-method (5 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,156 tokens. 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 2026-09-03.
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