Tracely is a CI/CD system for AI agents that turns failed production traces into replayable regression tests. Development teams use it to detect and group agent failures, run the resulting cases on pull requests, and block changes that reproduce those failures. The catalogue entries provide skills for operating this trace-based testing and observability workflow.
Borrowing it
Nothing to install: this file belongs to Jwuthri/Tracely-ai. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Jwuthri/Tracely-ai/master/.claude/skills/openseo-review-web-content/SKILL.mdgit clone --depth 1 https://github.com/Jwuthri/Tracely-aiWrote 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/jwuthri/tracely-ai/openseo-review-web-content)<a href="https://agentmods.dev/skills/jwuthri/tracely-ai/openseo-review-web-content"><img src="https://agentmods.dev/badge/skills/jwuthri/tracely-ai/openseo-review-web-content/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/jwuthri/tracely-ai/openseo-review-web-content"><img src="https://agentmods.dev/badge/skills/jwuthri/tracely-ai/openseo-review-web-content.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 | $0.00058 | $0.00811 |
| Opus 5 | $0.00029 | $0.00405 |
| Sonnet 5 | $0.00012 | $0.00162 |
| Haiku 4.5 | $0.00006 | $0.00081 |
Grade A, and why
openseo-review-web-content 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 11d 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.
This is a copy
100% identical to openseo-review-web-content — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 38 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenSEO Web Content
Everything we publish must be traceable to what the product actually does and costs, and must read like a practitioner wrote it. The reader's interest comes first: teach something they can act on, and answer straight — including when the honest answer is "no" or "it costs money."
Principles
- Traceable truth. Every capability claim, price, and screenshot is verifiable against the code, the fact sheet (
src/server/features/onboarding/openseo-fact-sheet.md), or the live product. If you can't point to where it's true, it doesn't ship. - Lead with the real answer. "No," "not unlimited," and "it costs money" are complete answers. Hedging that lets a reader infer something more flattering than the truth is a way of misleading them.
- Honest pricing, with its reasoning. Quality SEO data is expensive everywhere — that's why the big suites run $100/month and up. OpenSEO is the affordable option: $10/month, free to start. Never simply "free."
- Sound like a person. Fix AI tells by restating the underlying claim plainly, not by polishing the flourish. The deslop skill is the reference for what to hunt and how to fix it.
- Reader-first altitude. Guides teach actionable SEO that stands on its own — not product documentation, not generic filler. Credit free resources to their real owners (Google's autocomplete, the reader's own Search Console).
- One bar, whole surface. When a standard improves, sweep everything to it — all the FAQs, all the pages — not just the instance that got noticed.
- Playbook terminology. Call each approach within any OpenSEO playbook a "strategy," never a "play." Use "workflow" for the steps readers execute; use "playbook" only for the complete collection.
Questions to ask while reviewing
- If a reader trusted every claim and screenshot, then opened OpenSEO right now, where would reality not match?
- Does each answer open with the real answer, or quietly steer toward a more flattering inference?
- Read the sharpest line aloud: would a person say it that way?
- Is anything called free that actually costs credits?
- Is this teaching the reader something useful on its own, or drifting into product docs or padding?
- Does every link, image, and example on the page earn its place for the reader?
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.
- 11d ago First seen · 38 lines · 58 tokens per session scan A 52dc4858851d
openseo-review-web-content is a skill published in the GitHub repository Jwuthri/Tracely-ai (1,404 stars, last pushed yesterday), licensed MIT. It adds 58 tokens to every session and 811 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to openseo-review-web-content, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
architect-analyze
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gemini-review
Google Gemini CLI code review with Gemini 2.5 Pro, 1M token context, CI/CD integration.
squid-implement-night
Run the full agent-team pipeline end-to-end for one feature whose Tasks Plan is already approved by /squid-plan, handing the human a validated, ready-to-squash-merge PR. Trigger after /squid-plan.
pr-babysitter
Monitors or repairs an open GitHub PR: CI failures, conflicts, review threads, and merge readiness, reporting state changes. Use when asked to "watch this PR", "fix CI", "resolve conflicts", or "address review comments". For PR metadata use pr-creator; for npm release PRs use autoship.
tech-debt-ci-review
Codex adapter for deep technical-debt and CI-stability audits. Use when asked to find test theater, flaky tests, missing or mis-scoped tests, brittle CI/toolchain behavior, structural debt blocking green PRs, or a remediation order for opencode-swarm.
aster-review-ci
Run aster code reviews non-interactively in CI, GitHub Actions, or from another agent. Covers aster review --pr, --json, --stream, --comment, diff-from-stdin, token handling, and filtering findings. Use when wiring aster into a pipeline, posting PR comments, or parsing review output programmatically.