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/v0idos/performance-deity/telemetrynpx skills add v0idOS/performance-deity --skill telemetrygit clone --depth 1 https://github.com/v0idOS/performance-deityWhat 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 | $0.00037 | $0.00361 |
| Opus 5 | $0.00018 | $0.00180 |
| Sonnet 5 | $0.00007 | $0.00072 |
| Haiku 4.5 | $0.00004 | $0.00036 |
Grade A, and why
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 3d 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.
What it actually says
Execute all three phases in order.
Phase 1 — Trace Wrap
Wrap the critical-path function in a trace span:
OpenTelemetry:
tracer.startActiveSpan('operation.name', (span) => {
// ... function body
span.end();
});
Sentry:
const transaction = Sentry.startTransaction({ name: 'operation.name' });
// ... function body
transaction.finish();
Datadog:
tracer.trace('operation.name', () => {
// ... function body
});
Phase 2 — Attribute Injection
Inside the span, attach:
- Execution time (start and stop timer)
- Query tags:
user_id,tenant_id,endpoint - Input and output payload sizes in bytes
Phase 3 — Alert Rule
Propose an alert rule with all four fields specified:
| Field | Value |
|---|---|
| Metric | (e.g. trace.operation.duration) |
| Threshold | (e.g. > 200ms) |
| Evaluation window | (e.g. last 5 minutes) |
| Severity | (e.g. P2 / warning) |
Examples:
- Datadog:
avg(last_5m):avg:trace.operation.duration{env:prod} > 0.200→ P2 - Prometheus:
histogram_quantile(0.99, rate(http_request_duration_seconds_bucket[5m])) > 0.2→ warning
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.
- 3d ago First seen · 54 lines · 37 tokens per session scan A 02e559943ed9
telemetry is a skill published in the GitHub repository v0idOS/performance-deity (2 stars, last pushed 4mo ago), licensed MIT. It adds 37 tokens to every session and 361 once invoked, about $0.0002 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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