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 withoneai/one-agent-plugin --skill connecteamgit clone --depth 1 https://github.com/withoneai/one-agent-pluginWrote 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/withoneai/one-agent-plugin/connecteam)<a href="https://agentmods.dev/skills/withoneai/one-agent-plugin/connecteam"><img src="https://agentmods.dev/badge/skills/withoneai/one-agent-plugin/connecteam/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/withoneai/one-agent-plugin/connecteam"><img src="https://agentmods.dev/badge/skills/withoneai/one-agent-plugin/connecteam.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 | $0.00113 | $0.06154 |
| Opus 5 | $0.00056 | $0.03077 |
| Sonnet 5 | $0.00023 | $0.01231 |
| Haiku 4.5 | $0.00011 | $0.00615 |
Grade A, and why
connecteam 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 5d 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
77% identical to 2-chat — 277 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 — 254 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Connecteam through One
Connecteam is an employee management platform for deskless teams that provides scheduling, time tracking, task management, forms, training, onboarding, internal communication, and HR tools, allowing businesses to manage daily operations and workforce coordination from a single app.
One exposes Connecteam through four MCP tools. The table below carries real action ids from One's knowledge base, so for a common operation you can skip search and go straight to reading the action's parameters.
How to run an action
- Find the action in the table below, or call
search_one_platform_actionswith platformconnecteamif it is not listed. - Call
get_one_action_knowledgewith the action id. Do this every time, including for actions in this table. The table gives you the id, not the parameters. - Call
execute_one_actionwith parameters copied from that knowledge.
Never guess a parameter name, a body field, or an enum value. The knowledge has the real schema, and a guessed field is either a 400 or a silent write of the wrong thing.
Before you start
Call list_one_integrations once and confirm Connecteam is connected. If it is missing, the user has not connected it: say so and point them at https://app.withone.ai rather than reaching for raw HTTP.
Each connection carries an access field. If it reports {"policy": "methods", "methods": ["GET"]} the agent is read-only here, so plan a read-only answer instead of attempting a write that will be refused.
Before a write
Creates, updates, deletes and sends land on a real Connecteam account and cannot be recalled. State the action and the specific target in one line before the first write in a task, and let the user stop you. Reads need no confirmation.
Actions
Shifts
| Action | Method | Path | Action id |
|---|---|---|---|
| Get a Shift for a Scheduler | GET | /scheduler/v1/schedulers/{{schedulerId}}/shifts/{{shiftId}} |
conn_mod_def::GMSWSKpB2u4::xrZB-WYARruT3umizVn7Bg |
| List Shifts for a Scheduler | GET | /scheduler/v1/schedulers/{{schedulerId}}/shifts |
conn_mod_def::GMSWSMq56BE::zuSr2YDLSHCp4S1zKVaLVg |
| List Shifts for a Scheduler | GET | /scheduler/v2/schedulers/{{schedulerId}}/shifts |
conn_mod_def::GMSWSl5K4h8::FNjeuHgpQ_-jPEDk7WANYQ |
| Create Shifts for a Scheduler | POST | /scheduler/v1/schedulers/{{schedulerId}}/shifts |
conn_mod_def::GMSWSD6Lt0k::0uOTqctJSNiBLCggGg2aAg |
| Create Shifts for a Scheduler | POST | /scheduler/v2/schedulers/{{schedulerId}}/shifts |
conn_mod_def::GMSWSbwaxh0::JrMucw8PRIKpeHgzQtaGlw |
| Delete a Shift for a Scheduler | DELETE | /scheduler/v1/schedulers/{{schedulerId}}/shifts/{{shiftId}} |
conn_mod_def::GMSWSCniKm8::dhTIynqjSfiYwKz99bzzGw |
| Delete Shifts for a Scheduler | DELETE | /scheduler/v1/schedulers/{{schedulerId}}/shifts |
conn_mod_def::GMSWSDsCk9w::MUjlvqNoRzC0Jp17Cu6mdQ |
| Delete Shifts for a Scheduler | DELETE | /scheduler/v2/schedulers/{{schedulerId}}/shifts |
conn_mod_def::GMSWSWucAI8::3Zyk6hlVSfm_qi8h06scoA |
| Update Shifts for a Scheduler | PUT | /scheduler/v1/schedulers/{{schedulerId}}/shifts |
conn_mod_def::GMSWSO15uEU::j_kjPP-uRbW39biZ8STrcA |
| Update Shifts for a Scheduler | PUT | /scheduler/v2/schedulers/{{schedulerId}}/shifts |
conn_mod_def::GMSWSoD4P8k::cN8tOMiBTEySkcyJGmy7vw |
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.
- 5d ago First seen · 254 lines · 0 tokens per session scan A e78c89ad471a
connecteam is a skill published in the GitHub repository withoneai/one-agent-plugin (1 stars, last pushed 19d ago), licensed MIT. It adds 113 tokens to every session and 6,154 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 77% identical to 2-chat, differing in 277 lines, and is treated as a copy.
Other skills, from other repositories
things-mac
Manage Things 3 via the things CLI on macOS (add/update projects+todos via URL scheme; read/search/list from the local Things database). Use when a user asks Otto to add a task to Things, list inbox/today/upcoming, search tasks, or inspect projects/areas/tags.
gsd-ns-manage
Route to the appropriate management skill based on the user's intent. gsd-config (settings + advanced + integrations + profile) and gsd-workspace (new + list + remove) are post-#2790 consolidated entries.
slack-tools
Slack workspace management and automation specialist.
ceo-setup
One-time onboarding for the executive/manager commitment workflow — delegation-heavy, meeting prep, decision capture, morning and evening digests. Creates a commitments project and installs two dashboard widgets. After successful setup this skill is excluded from selection until the marker file is deleted.
service-desk
Runs the IT service desk — intake, triage, prioritization, escalation, knowledge, and the metrics that improve service rather than distort it. Use this to set up or fix a service desk, design ticket priority and escalation, reduce repeat contacts, structure a knowledge base, or work out why a desk hitting its targets…
10-todo
Split the user prompt into independent todos and run one executor agent per todo in parallel, then report a minimal table. Use when the user says "todo" or asks to fan out a multi-part request into parallel implementations.