A daily project status check that asks each team role for a red, yellow, or green status and reports blockers first. It also checks whether the project has been onboarded and uses its deployment tier when judging issues.

Use it for daily project updates, blocker reporting, and checking project-wide health across team roles.

It gives the product owner a short view of what is delivering value, what is blocked, and what needs attention without turning the meeting into planning or review.

standup — Skill for Claude Code by MotWakorb

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 MotWakorb/ai-agent-dev-team --skill standup

Clone the repo

git clone --depth 1 https://github.com/MotWakorb/ai-agent-dev-team

Made for: Claude Code.

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/motwakorb/ai-agent-dev-team/standup.svg)](https://agentmods.dev/skills/motwakorb/ai-agent-dev-team/standup)

Your own site

<a href="https://agentmods.dev/skills/motwakorb/ai-agent-dev-team/standup"><img src="https://agentmods.dev/badge/skills/motwakorb/ai-agent-dev-team/standup.svg" alt="Measured on agentmods" height="20"></a>

Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,676 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.

Model	Per session	Once invoked
Fable 5.1	$0.00037	$0.02676
Opus 5	$0.00018	$0.01338
Sonnet 5	$0.00007	$0.00535
Haiku 4.5	$0.00004	$0.00268

Measured 7d ago against content hash 5270fccf0292, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

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 7d 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.

standup/SKILL.md · 209 lines

How it starts

The opening of the file, as written. The whole thing — 209 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Daily Standup

Fast. Focused. User value first, blockers second. If everything is green, say so and move on. This is not a planning session, not a review, not a retro. This is "are we delivering user value, what's stuck, what does the PO need to know right now."

Preflight: Verify Onboarding & Effective Tier

Before any other step, verify deployment-tier setup. Defaulting to enterprise rigor across the board is the failure mode this preflight prevents.

Check COMPONENTS.md exists at the repo root. If missing, refuse to run and tell the PO:

This project hasn't been onboarded yet. Run /onboard first — it produces COMPONENTS.md, which records each component's deployment tier. Without it, the standup will surface home-lab components as RED for missing enterprise practices. See _shared/deployment-tier.md for the tier model.

Do not proceed.
Read COMPONENTS.md to know each component's tier. The standup is project-wide, so all components are in scope, but each is rated against its own tier — a home-lab metrics stack is not RED for missing SLOs.

Inject tier context into every agent prompt. Every prompt below must additionally include:

Read ~/.claude/skills/_shared/deployment-tier.md.
Components and tiers in this project: [component] ([tier]), ...
When rating R/Y/G, calibrate to each component's tier. A home-lab component is not YELLOW for missing enterprise baseline expectations — it's GREEN if it meets its own tier's baseline. Only flag concerns relative to the component's own tier.

Model Selection

When spawning agents, pass model: explicitly per _shared/orchestration.md (Agent Model Selection). For this skill:

Phase 1 (all 10 identity.md triage agents): haiku — short, formulaic R/Y/G across many parallel agents
Phase 2 (non-green deep assessment, 1-3 agents): sonnet — needs depth on a small number of personas

Tier modulation applies to Phase 2 only. If a persona is assessing a home-lab component, downshift to haiku — except security-engineer, which holds at sonnet (a home-lab CVE is still a CVE).

Read the full file on GitHub · 209 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.

7d ago First seen · 209 lines · 37 tokens per session scan A 5270fccf0292

Subscribe to this mod's changes

standup is a skill published in the GitHub repository MotWakorb/ai-agent-dev-team (2 stars, last pushed 25d ago), licensed MIT. It adds 37 tokens to every session and 2,676 once invoked, about $0.0002 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 2026-08-31.

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