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 wyattowalsh/agents --skill observability-advisorgit clone --depth 1 https://github.com/wyattowalsh/agentsWrote 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/wyattowalsh/agents/observability-advisor)<a href="https://agentmods.dev/skills/wyattowalsh/agents/observability-advisor"><img src="https://agentmods.dev/badge/skills/wyattowalsh/agents/observability-advisor/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/wyattowalsh/agents/observability-advisor"><img src="https://agentmods.dev/badge/skills/wyattowalsh/agents/observability-advisor.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 | $0.00043 | $0.02306 |
| Opus 5.5 | $0.00017 | $0.00922 |
| Sonnet 5.5 | $0.00009 | $0.00461 |
| Haiku 4.5 | $0.00004 | $0.00231 |
Grade A, and why
observability-advisor 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 — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Observability Advisor
Design and review telemetry that helps teams detect, diagnose, and improve service behavior before and during reliability problems.
Scope: Vendor-neutral observability architecture, signal design, coverage reviews, SLOs, alerting, and instrumentation plans. NOT for live incident coordination (incident-response-engineer), deep runtime bottleneck profiling (performance-profiler), or CloudWatch-specific implementation details (cloudwatch).
Canonical Vocabulary
| Term | Definition |
|---|---|
| telemetry | Logs, metrics, traces, profiles, and events emitted by a system |
| signal | A measurable indicator used to detect or explain behavior |
| metric | Numeric time-series measurement aggregated over time |
| log | Structured event record capturing context for a specific occurrence |
| trace | End-to-end record of work moving through distributed components |
| span | A timed unit of work within a trace |
| SLI | Concrete measurement of a user-relevant reliability property |
| SLO | Target threshold and window for an SLI |
| error budget | Allowed unreliability implied by an SLO over its window |
| cardinality | Number of unique label or attribute values attached to telemetry |
Dispatch
| $ARGUMENTS | Mode |
|---|---|
design <system> |
Design an observability architecture for a service or workflow |
review <service or stack> |
Audit existing telemetry, dashboards, and alerts |
instrument <service or path> |
Plan what to emit and where to add instrumentation |
alert <service or journey> |
Design actionable alerting and escalation |
slo <service or journey> |
Define SLIs, SLOs, and error budget policy |
investigate <signal or symptom> |
Structure cross-signal diagnosis for an issue |
| Natural language about logs, metrics, traces, dashboards, or alerting | Auto-detect the closest mode |
| Empty | Show the mode menu with examples |
When to Use
- A team can see failures but cannot explain them quickly
- Alerts are noisy, late, or missing user-impact context
- A service lacks clear SLIs, SLOs, or error budget policy
- You need to add instrumentation to a new service, workflow, or migration
- Dashboards exist but ownership, escalation, or runbook linkage is weak
What ships with it
14 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- evals/evals.json 5.1 KB
- references/alert-anti-patterns.md 2.1 KB
- references/investigation-workflows.md 2.0 KB
- references/output-templates.md 2.0 KB
- references/signal-selection-matrix.md 2.5 KB
- references/sli-slo-examples.md 1.9 KB
- scripts/asset_toolkit/__init__.py 303 B runs code
- scripts/asset_toolkit/_shared.py 5.6 KB runs code
- scripts/asset_toolkit/common.py 3.0 KB runs code
- scripts/asset_toolkit/package.py 43 KB runs code
- scripts/asset_toolkit/validate_evals.py 11 KB runs code
- scripts/asset_toolkit/validate_hooks.py 13 KB runs code
- scripts/asset_toolkit/validate_skill.py 3.6 KB runs code
- scripts/check.py 2.2 KB runs code
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 · 197 lines · 43 tokens per session scan A 555356277562
observability-advisor is a skill published in the GitHub repository wyattowalsh/agents (5 stars, last pushed 1mo ago), licensed MIT. It adds 43 tokens to every session and 2,306 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-03.
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