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 skills add adrielp/ai-engineering-harness --skill otel_ottlgit clone --depth 1 https://github.com/adrielp/ai-engineering-harnessWrote 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/adrielp/ai-engineering-harness/otel_ottl)<a href="https://agentmods.dev/skills/adrielp/ai-engineering-harness/otel_ottl"><img src="https://agentmods.dev/badge/skills/adrielp/ai-engineering-harness/otel_ottl/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/skills/adrielp/ai-engineering-harness/otel_ottl"><img src="https://agentmods.dev/badge/skills/adrielp/ai-engineering-harness/otel_ottl.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 | $0.00042 | $0.02218 |
| Opus 5 | $0.00021 | $0.01109 |
| Sonnet 5 | $0.00008 | $0.00444 |
| Haiku 4.5 | $0.00004 | $0.00222 |
Grade A, and why
otel_ottl 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 9d 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 — 250 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenTelemetry Transformation Language (OTTL)
You are an OTTL expert. Produce production-grade expressions with error_mode: ignore and proper where guards. Always use the transform processor for mutations and filter processor for drops.
1. Where OTTL Is Used
| Component | Type | OTTL Role |
|---|---|---|
transform |
Processor | Statements with conditions |
filter |
Processor | Drop conditions |
routing |
Processor/Connector | Routing conditions |
signaltometrics |
Connector | Attribute expressions, conditions |
2. Syntax
Contexts
| Context | Key Paths | Signal |
|---|---|---|
resource |
resource.attributes[...] |
All |
scope |
scope.name, scope.version, scope.attributes[...] |
All |
span |
name, kind, status.code, status.message, attributes[...], duration, start_time_unix_nano |
Traces |
spanevent |
name, attributes[...], timestamp |
Traces |
metric |
name, description, unit, type |
Metrics |
datapoint |
value_int, value_double, attributes[...], time_unix_nano |
Metrics |
log |
body, severity_number, severity_text, attributes[...], trace_id, span_id |
Logs |
Operators
==, !=, >, <, >=, <=, and, or, not
Enumerations
SPAN_KIND_INTERNAL | SPAN_KIND_SERVER | SPAN_KIND_CLIENT | SPAN_KIND_PRODUCER | SPAN_KIND_CONSUMER
STATUS_CODE_UNSET | STATUS_CODE_OK | STATUS_CODE_ERROR
SEVERITY_NUMBER_TRACE=1 | DEBUG=5 | INFO=9 | WARN=13 | ERROR=17 | FATAL=21
3. Common Patterns
Set Attributes
processors:
transform:
trace_statements:
- context: span
statements:
- set(attributes["processed_by"], "collector-v1")
- set(attributes["env"], resource.attributes["deployment.environment.name"])
- set(attributes["is_error"], true) where status.code == STATUS_CODE_ERROR
Redact Sensitive Data
processors:
transform:
error_mode: ignore
trace_statements:
- context: span
statements:
# Headers
- delete_key(attributes, "http.request.header.authorization")
- delete_key(attributes, "http.request.header.cookie")
- delete_key(attributes, "http.request.header.set-cookie")
- delete_key(attributes, "http.request.header.x-api-key")
# DB queries — strip parameter values
- replace_pattern(attributes["db.query.text"], "'[^']*'", "'?'") where attributes["db.query.text"] != nil
# URL query params
- replace_pattern(attributes["url.query"], "(?i)(token|key|secret|password|auth)=[^&]*", "$1=[REDACTED]") where attributes["url.query"] != nil
# Credit cards
- replace_pattern(attributes["payment.card"], "\\d{12,19}", "[REDACTED]")
# Emails
- replace_pattern(attributes["user.email"], "[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\\.[a-zA-Z]{2,}", "[REDACTED]")
# Generic secrets in values
- replace_pattern(attributes["config"], "(?i)(password|secret|token|api_key)\\s*[=:]\\s*\\S+", "$1=[REDACTED]")
log_statements:
- context: log
statements:
- replace_pattern(body, "(?i)(password|secret|token|api[_-]?key|authorization)\\s*[=:]\\s*\\S+", "$1=[REDACTED]")
- replace_pattern(body, "\\b\\d{4}[- ]?\\d{4}[- ]?\\d{4}[- ]?\\d{4}\\b", "[CARD-REDACTED]")
- replace_pattern(body, "[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\\.[a-zA-Z]{2,}", "[EMAIL-REDACTED]")
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.
- 9d ago First seen · 250 lines · 42 tokens per session scan A c91372c3d25a
otel_ottl is a skill published in the GitHub repository adrielp/ai-engineering-harness (20 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 42 tokens to every session and 2,218 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 2026-08-30.
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