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 yimwoo/codex-agenteam --skill standupgit clone --depth 1 https://github.com/yimwoo/codex-agenteamWrote 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/yimwoo/codex-agenteam/standup)<a href="https://agentmods.dev/skills/yimwoo/codex-agenteam/standup"><img src="https://agentmods.dev/badge/skills/yimwoo/codex-agenteam/standup/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/yimwoo/codex-agenteam/standup"><img src="https://agentmods.dev/badge/skills/yimwoo/codex-agenteam/standup.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 | $0.00025 | $0.01380 |
| Opus 5.5 | $0.00010 | $0.00552 |
| Sonnet 5.5 | $0.00005 | $0.00276 |
| Haiku 4.5 | $0.00003 | $0.00138 |
Grade A, and why
standup 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 1mo 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 — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AgenTeam Standup
Produce a fast, Linear-style project status report by reading the current run state, role artifacts, and git activity. This skill does not dispatch subagents -- the lead agent reads everything directly and synthesizes.
Process
1. Auto-Init Guard
Check for .agenteam/config.yaml, .agenteam.team/config.yaml, or legacy
agenteam.yaml in the project root. If all are missing:
- Create config dir:
mkdir -p .agenteam - Copy the template:
cp <plugin-dir>/templates/agenteam.yaml.template .agenteam/config.yaml - Set the team name to the project directory name
- Generate agents:
python3 <runtime>/agenteam_rt.py generate - Tell the user: "AgenTeam auto-initialized with default roles. Edit
.agenteam/config.yamlto customize."
2. Gather State
Call the runtime to assemble run state, health indicator, and artifact paths:
python3 <runtime>/agenteam_rt.py standup
Capture the JSON output. Expected fields:
health--on-track,at-risk,off-track, orno-active-runrun_id-- current run identifier (may be null if no active run)task-- task descriptionstages-- list of stages with status, assigned role, and gate stateartifact_paths-- map of role name to artifact directorygovernance.adoption-- optional summary of decisions, escalations, tripwire checks, gate rejections, and criteria overridesoutput_path-- where to write the final report (e.g.,docs/meetings/<timestamp>-standup.md)- Active attempt details --
thread_id, last heartbeat and heartbeat age, idle budget and wall budget remaining, retry count, and stop reason
3. Read Role Artifacts
For each role in artifact_paths, check what exists in that directory
and produce a one-line summary:
| Role | Artifact Directory | Look For |
|---|---|---|
| researcher | docs/research/ |
Research reports, dated findings |
| pm | docs/strategies/ |
Strategy docs, roadmaps, specs |
| architect | docs/designs/ |
Design docs, architecture decisions |
| dev | src/**, docs/plans/ |
Source files changed, plan docs |
| qa | tests/** |
Test files, coverage reports |
| reviewer | (read-only) | Review comments in state files |
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.
- 1mo ago First seen · 171 lines · 25 tokens per session scan A 3b8d50e49be4
standup is a skill published in the GitHub repository yimwoo/codex-agenteam (14 stars, last pushed 3mo ago), licensed MIT. It adds 25 tokens to every session and 1,380 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
linear-tickets
Create or update high-quality Linear tickets while preserving the originating report, diagnostic links, attachments, and reporter/requester attribution. Read this whenever someone asks to create, recreate, or update a Linear issue.
commonly
You are a member of a Commonly workspace — a shared space where humans and AI agents from any origin collaborate in pods (chat rooms with memory). Use this whenever you are connected to Commonly via the commonly MCP tools: to read what's happening, post, remember things across sessions, react, DM other agents, and…
launch
Planning releases and reporting delivery work from GitHub PR history. Use when versioning, CHANGELOGs, rollout or rollback plans, engineering metrics, retrospectives, or stakeholder reports are needed.
pdm
Navigating delivery status read-only: reconciles planned scope (specs/roadmap/PRD) against implemented code for what's built vs left. Not for priority scoring (Rank) or AC conformance (Attest).
sherpa
Guiding workflows by decomposing complex tasks (Epics) into Atomic Steps under 15 minutes each, with progress tracking and drift prevention. Use when complex decomposition is needed.
rank
Quantifying priority by scoring competing items with ICE/RICE/WSJF/MoSCoW/Cost of Delay/Kano. No code. Use to prioritize features/bugs/initiatives or arbitrate Must vs Should at MVP scoping.