GitHub Agentic Workflows is a GitHub CLI extension that lets developers define AI-assisted repository automation in Markdown and run it through GitHub Actions. It is intended for tasks requiring interpretation or reasoning, such as issue triage, pull-request review, CI investigation, documentation maintenance, and dependency analysis. The catalogue entries provide skills and agents for working with these workflows.
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 github/gh-aw --skill otel-queriesgit clone --depth 1 https://github.com/github/gh-awWrote 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/github/gh-aw/otel-queries)<a href="https://agentmods.dev/skills/github/gh-aw/otel-queries"><img src="https://agentmods.dev/badge/skills/github/gh-aw/otel-queries/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/github/gh-aw/otel-queries"><img src="https://agentmods.dev/badge/skills/github/gh-aw/otel-queries.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 46 Skill instructs the agent to never refuse or to always comply. Suppressing the agent's ability to decline removes a core safety control and enables downstream harmful requests to succeed.Fix: Remove any instruction telling the agent to never refuse or always comply. The agent must retain the ability to decline unsafe, out-of-scope, or harmful requests.
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 | $0.00020 | $0.01998 |
| Opus 5.5 | $0.00008 | $0.00799 |
| Sonnet 5.5 | $0.00004 | $0.00400 |
| Haiku 4.5 | $0.00002 | $0.00200 |
Grade A, and why
otel-queries 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 — 289 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OTel Queries
Use this skill to inspect gh-aw OpenTelemetry/OTLP data and answer telemetry questions without re-deriving trace fields, backend filters, and diagnostics.
When To Use
Use this skill for requests such as:
- analyze OTEL or OTLP data
- inspect traces in Grafana, Tempo, Sentry, Honeycomb, or Datadog
- explain why a workflow or agent run is slow or failing
- compare run phases, error clusters, or span attributes
- identify the best observability or performance improvement
- close the loop from telemetry into code or workflow changes
Do not use this skill for instrumentation-only tasks that do not require reading telemetry. For pure emit-side work, start with the existing OTLP code and docs.
Primary Goal
Reduce a broad telemetry task to one tight loop:
- Find the cheapest trustworthy telemetry source.
- Run a small fixed set of common queries.
- Confirm one concrete bottleneck, missing attribute, or broken correlation path.
- Answer the user's telemetry question directly.
- Recommend or implement a follow-on optimization only when the evidence supports it.
Telemetry Sources In Priority Order
Prefer sources in this order unless the user says otherwise:
- Local artifacts or mirrors already in the workspace.
/tmp/gh-aw/otel.jsonlfor gh-aw spans.- Live OTLP backend data through an MCP server or supported tool — Copilot CLI spans are exported directly to the configured OTLP backend (no local file mirror) and must be queried there, filtered by the
github.run_idresource attribute. - Static code inspection only, when no telemetry is available.
Use the cheapest source that can disconfirm the current hypothesis.
Standard Analysis Loop
Always answer these questions in order before expanding scope.
1. Do spans exist for the run or workflow at all?
Look for:
traceId- span
name service.namegithub.repositorygithub.run_id
If these are missing, the problem is likely export, filtering, or trace propagation rather than optimization.
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 Changed fd600f1c01f3
- 2mo ago First seen · 289 lines · 20 tokens per session scan A 70b356501454
otel-queries is a skill published in the GitHub repository github/gh-aw (5,579 stars, last pushed yesterday), licensed MIT. It adds 20 tokens to every session and 1,998 once invoked, about $0.0001 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 2026-08-30.
otel-queries compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| otel-queriesgithub/gh-aw | Skill | 5.6k | yesterday | MIT | A | 20 | Claude Code, Codex |
| watch-prjustincampbell/gh-watch | Skill | 4 | 7d ago | MIT | A | 48 | Claude Code |
| watch-tagjustincampbell/gh-watch | Skill | 4 | 7d ago | MIT | A | 62 | Claude Code |
| watch-branchjustincampbell/gh-watch | Skill | 4 | 7d ago | MIT | A | 45 | Claude Code |
| watch-commitjustincampbell/gh-watch | Skill | 4 | 7d ago | MIT | A | 48 | Claude Code |
| c-githubdaxaur/openpaw | Skill | 177 | 5mo ago | MIT | A | 48 | Claude Code, Codex |
| update-architecture-docsAlexSkrypnyk/scaffold | Skill | 11 | yesterday | GPL-3.0 | A | 46 | Claude Code |