opengeni-schedules

opengeni-schedules is a skill for Claude Code, Codex from Cloudgeni-ai/opengeni. It costs 62 tokens per session (1,077 once invoked), scanned A, original, Apache-2.0.

A workflow for creating recurring tasks, reminders, schedules, or monitors in OpenGeni. It checks existing tasks and discovers the repositories, credentials, and integrations that the work needs.

In plain words
What is it for?
Use it to schedule repository work, monitoring, or other recurring tasks with the right timing, time zone, and connected resources.
Why use it?
It reduces duplicate schedules and prevents secret values or unverified integrations from being placed into task setup.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to schedule repository work, monitoring, or other recurring tasks with the right timing, time zone, and connected resources.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/cloudgeni-ai/opengeni/opengeni-schedules
Install

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.

Any agent
npx skills add Cloudgeni-ai/opengeni --skill opengeni-schedules
Clone the repo
git clone --depth 1 https://github.com/Cloudgeni-ai/opengeni

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for opengeni-schedules

README.md
[![agentmods](https://agentmods.dev/badge/skills/cloudgeni-ai/opengeni/opengeni-schedules/github.svg)](https://agentmods.dev/skills/cloudgeni-ai/opengeni/opengeni-schedules)
Your own site
<a href="https://agentmods.dev/skills/cloudgeni-ai/opengeni/opengeni-schedules"><img src="https://agentmods.dev/badge/skills/cloudgeni-ai/opengeni/opengeni-schedules/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.

agentmods 80×15 button for opengeni-schedules

Your own site · 80×15
<a href="https://agentmods.dev/skills/cloudgeni-ai/opengeni/opengeni-schedules"><img src="https://agentmods.dev/badge/skills/cloudgeni-ai/opengeni/opengeni-schedules.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 62 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,077 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00062 $0.01077
Opus 5.5 $0.00025 $0.00431
Sonnet 5.5 $0.00012 $0.00215
Haiku 4.5 $0.00006 $0.00108

Measured 2d ago against content hash 1d909fcd72ed, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

opengeni-schedules 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 2d 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.

packages/runtime/src/bundled_schedule_skills/opengeni-schedules/SKILL.md · 94 lines

How it starts

The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Create a schedule

Turn the user's description into scheduled work in the current workspace. Research what is available before asking questions. Ask only for essential details you cannot discover or reasonably decide from the request.

Choose the destination

By default, schedule a message in this conversation. “Remind me”, “check later”, “keep watching” and “schedule yourself” mean continue this chat. Supply name, schedule and prompt; the tool resolves the current chat from its signed context. Choose another existing chat with targetSessionId only when requested. Its model, tools, machine and attachments apply at run time, so do not copy those settings into the schedule.

Use reusable_session or new_session_per_run with agentConfig only when the user requests separate-agent work. Sessionless calls require an explicit destination or a separate-agent mode.

Discover what the task needs

  • Use scheduled_tasks_list to avoid duplicating an existing schedule. Follow pagination when needed and use scheduled_tasks_get for a relevant task's details. A list summary is not its complete configuration.
  • If the work needs a repository, use github_repositories_list to find the authorized repository and select the required resources.
  • If the scheduled agent needs credentials, use secret_search to find the saved item and write its reference (for example {{secret:GitHub/token}}) in the prompt. Save it to the workspace with secret_save or secret_move when the schedule runs without you; never copy secret values into prompts.
  • If it needs an integration such as Slack or Sentry, use capability_catalog_search and the available tool discovery to find the capability and exact operations. Follow returned connection/setup and approval requirements. Do not claim that discovery means the integration is ready.

Select only the resources and tools the task needs; saved secrets are used by {{secret:…}} reference and need no attachment. Missing optional dependencies are not a reason to ask for unnecessary setup. If a required capability or authority is unavailable, explain the remaining setup briefly instead of inventing a tool or borrowing another person's connection.

Read the full file on GitHub · 94 lines

Changes

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.

  1. 2d ago Changed · +4 lines 1d909fcd72ed
  2. 7d ago Changed 2196bae0c3b5
  3. 12d ago Changed · +33 lines 612b07c75c4b
  4. 13d ago First seen · 57 lines · 62 tokens per session scan A 260a4f348865

Subscribe to this mod's changes

opengeni-schedules is a skill published in the GitHub repository Cloudgeni-ai/opengeni (202 stars, last pushed today), licensed Apache-2.0. It adds 62 tokens to every session and 1,077 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 2026-10-03.

Related

Other skills, from other repositories

add-a-lib

Scaffold a new shared library under libs/ in the builders-stack monorepo. Use when code is needed in two or more places (apps or services) and should become a single source of truth consumed by package name. Covers the package.json, tsconfig, the one-public-door src/index.ts barrel, and wiring it into a consumer…

lonormaly/builders-stack · 81 tokens

github

A guide to using GitHub CLI, a command-line tool for working with GitHub repositories. It covers issues, pull requests, releases, labels, milestones, and workflow runs.

DaleStudy/skills · 133 tokens

review-skill-suggestions

Review proposed improvements to the skills in an explicit Speakeasy AI Control Plane project, then approve, partially approve, correct, or dismiss each one with the user's confirmation. Use when someone asks which skills have suggested changes waiting, wants to work through the suggestion queue, or wants to accept or…

speakeasy-api/gram · 72 tokens

autogpt-agents

Autonomous AI agent platform for building and deploying continuous agents. Use when creating visual workflow agents, deploying persistent autonomous agents, or building complex multi-step AI automation systems.

synthetic-sciences/openscience · 39 tokens

pn-create-workflow-roadmap

Generate a project workflow roadmap (docs/WORKFLOW.md) mapping plan phases to pn-core commands with model tier recommendations and per-step token cost estimates. Runs after pn-writing-plans.

perniemann/pnCore · 44 tokens

pn-program-orchestration

Conductor for featureprogram: split ≥2 vertical slices, DAG, merge queue. Use when the user asks for parallel slices or /pn-program — not for a single-slice feature.

perniemann/pnCore · 44 tokens