Entry point + orchestrator for the recomby-geo GEO (Generative Engine Optimization) workflow on OpenAI Codex CLI. Use when the user wants to run any stage of the GEO pipeline on a client folder — intake, visibility audit, content-gap analysis, content brief, draft production, distribution, or monthly re-audit — or asks to "run GEO", "audit AI search visibility", or "GEO this client". Codex has no bare slash commands, so this skill is how the 7 stages (that Claude Code runs as /01-intake … /07-reaudit) are driven on Codex. It routes to the per-stage specs in this plugin's commands/ and enforces the orchestration rules. Does not auto-fill expert content — the human-in-loop brief checkpoint is the moat.
npx skills add https://github.com/ViryaZheng/recomby-geo --skill geo-pipeline
On Claude Code each stage is a bare slash command (/01-intake …
/07-reaudit). Codex CLI has no bare custom commands, so this skill is the
Codex entry point: it carries the orchestration rules and routes to the
per-stage specification files, which are the single source of truth
shared with the Claude Code side. Do not duplicate stage logic here — read
the stage file and follow it.
Per-stage specs (read the one you're running):
commands/01-intake.md, commands/02-audit.md, commands/03-gap.md,
commands/04-content-brief.md, commands/05-production.md,
commands/06-distribution.md, commands/07-reaudit.md (relative to this
plugin's root). Full directory convention + dependency graph:
orchestrator/run.md.
clients/<slug>/ and the stage the user wants.commands/0X-*.md and execute its Procedure verbatim.moving on (Codex has no built-in schema validation — run it explicitly):
python3 - <<'PY'
import json, jsonschema
pairs = {
"brand_context.json": "brand_context.schema.json",
"visibility_baseline.json": "visibility_baseline.schema.json",
"content_priorities.json": "content_priorities.schema.json",
} # see schemas/ for the full set incl. attribution_diff + review_feedback
# jsonschema.Draft202012Validator(json.load(open("plugins/recomby-geo/schemas/<file>"))).validate(json.load(open("clients/<slug>/<artifact>")))
print("validate each artifact against plugins/recomby-geo/schemas/*.schema.json")
PY
inputs/ → 01-intake → brand_context.json
→ 02-audit → visibility_baseline.json
→ 03-gap → content_priorities.json
→ 04-content-brief → briefs/<id>.md (+ .html, REQUIRED-FILL slots)
[EXPERT FILLS THE SLOTS — not the AI]
04 Step 9 verifies fills → status: ready-for-production
→ 05-production → drafts/<id>.md (+ review .html)
→ 06-distribution → distribution/<id>.json + publish-bundle.md
[PUBLISH + WAIT 7+ days]
→ 07-reaudit (monthly) → reaudit/round-N.json → feeds next 03-gap
02 needs 01; 03 needs 01+02; 04 needs 01+03; 05 needs 04 (filled); 06 needs
05; 07 needs a prior 02.
05-production refuses to rununless briefs/<id>.meta.json status is ready-for-production. Never
auto-fill REQUIRED-FILL slots; pause the pipeline if the expert is
unavailable. This human-in-loop checkpoint is the entire moat.
before moving on. Schemas: schemas/*.schema.json.
clients/<slug>/folders or factor out "common" context.
Stages 04 and 05 produce interactive HTML for the client via the
geo-review-html skill (also in this plugin). On Codex this works the same
as on Claude Code — the stage spec already calls render_html.py.
The capability skills' scripts (e.g. seo-geo-optimizer, geo-review-html)
need python3 on PATH; the schema validation step needs jsonschema
(pip install jsonschema). These are the same dependencies as the Claude
Code side.
Complete development kit for Microsoft 365 Copilot declarative agents with three comprehensive workflows (basic, advanced, validation), TypeSpec support, and Microsoft 365 Agents Toolkit integration
Format and structurally validate local treatment-plan documentation after clinical decisions have already been supplied and verified by authorized licensed professionals. Use for source traceability, clinician-authored intervention records, goals and checkpoints, shared-decision records, reconciliation handoffs, and release gates—not for clinical decision-making.
> provider/change budget/修改卖家/修改预算/draft/草稿/我的任务/my tasks/what am I working on/关闭/取消任务/决策列表/decision list/指定服务商/browse (sender.role = COUNTERPARTY, not you); (3) literal "Read the okx-ai skill" (or legacy "Read the okx-agent-task skill") in the envelope.
Automate payer review of prior authorization (PA) requests. This skill should be used when users say "Review this PA request", "Process prior authorization for [procedure]", "Assess medical necessity", "Generate PA decision", or when processing clinical documentation for coverage policy validation and authorization decisions.
Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration.
Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability.
Orchestrates design workflows by routing work through brainstorming, multi-agent review, and execution readiness in the correct order.
Structured persuasion for tech leads, PMs, and founders—not activity logs. Five scenarios (kickoff, status update, wrap-up, investor pitch, solution selling) on one 5-part framework (Hook→Context→Proposal→Evidence→Ask). AI prompts for missing materials and audience context; pre-submit checklist. Claude Code plugin; Cursor, Codex, and chat via prompts.
Take viryazheng/geo-pipeline from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference pip.
Without those the skill loads but fails at the first command.