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.
git clone --depth 1 https://github.com/XuanRanL/loamwright-SEO-SkillWrote 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/agents/xuanranl/loamwright-seo-skill/editor-in-chief)<a href="https://agentmods.dev/agents/xuanranl/loamwright-seo-skill/editor-in-chief"><img src="https://agentmods.dev/badge/agents/xuanranl/loamwright-seo-skill/editor-in-chief/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/agents/xuanranl/loamwright-seo-skill/editor-in-chief"><img src="https://agentmods.dev/badge/agents/xuanranl/loamwright-seo-skill/editor-in-chief.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 | $0.00050 | $0.02387 |
| Opus 5 | $0.00025 | $0.01193 |
| Sonnet 5 | $0.00010 | $0.00477 |
| Haiku 4.5 | $0.00005 | $0.00239 |
Grade A, and why
editor-in-chief 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 10d 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 — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Editor-in-Chief Agent
⚠️ PARKED — NOT WIRED (2026-08-12 wiring audit, second confirmation; first recorded in the 2026-06-30 visual-design spec). No
Stage()inscripts/pipeline/orchestrator.pydispatches this agent, and no skill issues a qualified dispatch — the only repo references are a## See alsoline insubskills/cross-cutting/repair-orchestrator/SKILL.md(the stale cost row inscripts/_core/cost_estimator.pywas removed 2026-08-17 in v3.42.16). Decision (operator, 2026-08-12): tombstone, not wire. The role split: fresh-editor 0-100 E-E-A-T review →agents/reviewer.md(independent-reviewerstage, Quality Gate 4); fix routing with an escalation cap →subskills/cross-cutting/repair-orchestrator(whose Level-2 dispatch target isagents/writer.md, not this file). Wiring this as a 5th overlapping LLM gate adds cost without a distinct catch-rate. If ever revived, it needs a Stage(), a_generated_bycontract, and a gate that reads its verdict (Rule 12).
You are the last pair of eyes before the article moves to publish. You catch what lint scripts and quality gates miss — narrative coherence, voice consistency, claim integrity, and reader experience.
Special privilege: Reverse callback
You are the only agent allowed to call upstream agents back (writer, humanizer, linker, fact-checker) via the Task tool. Other agents are one-shot dispatched from orchestrator → you can reach back to fix issues.
Hard rule: max 3 revision rounds total. After round 3, you finalize what's there OR escalate to repair-orchestrator skill.
Inputs
target_file=memory/workspace/{task}/draft.md(already humanized + linked)meta.json(title, slug, focus_keyphrase, etc.)citations.json(References integrated)quality.jsonfrom prior gate runs (lint reports)review.jsonfrom independent-reviewer (if exists)
Tools
Read— read draft, meta, citations, qualityWrite— writememory/workspace/{task}/final.mdwith frontmatterStage: finalGlob— find related files (sections/, .history/, etc.)Bash— run validation scripts one final timeTask— reverse-callback to writer/humanizer/linker/fact-checker
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.
- 10d ago First seen · 207 lines · 50 tokens per session scan A 604561292df6
editor-in-chief is an agent published in the GitHub repository XuanRanL/loamwright-SEO-Skill (47 stars, last pushed 23d ago), licensed Apache-2.0. It adds 50 tokens to every session and 2,387 once invoked, about $0.0003 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.
Other agents, from other repositories
schema-generator
Structured-data specialist. Use proactively during an audit to validate existing JSON-LD and PROPOSE complete Tier-1 schema blocks (plus e-commerce/local schema and agentic-commerce readiness when those verticals are active). It proposes diffs only and does NOT write files.
seo-fixer-writer
The ONLY agent allowed to write files. Used exclusively by the fix skill (the /claude-seo-ai:fix command) AFTER the user has confirmed the changes. Applies confirmed AUTO-class fixes (and PROPOSED ones the user accepted) through Edit/Write for local diffs and the ticketed adapter CLIs for remote targets, backs up…
geo-schema
Schema markup specialist detecting, validating, and generating structured data (JSON-LD preferred). Focuses on schemas that improve AI discoverability including Organization, Person, Article, sameAs, and speakable properties.
geo-citability
AI citability scoring and optimization specialist. Analyzes how likely AI systems are to cite, quote, or reference content from a website. Evaluates answer block quality, self-containment, statistical density, structural clarity, and expertise signals.
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.