Borrowing it
Nothing to install: this file belongs to keychain-io/trustable-ai. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/keychain-io/trustable-ai/main/.claude/commands/daily-standup.mdgit clone --depth 1 https://github.com/keychain-io/trustable-aiWrote 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/commands/keychain-io/trustable-ai/daily-standup)<a href="https://agentmods.dev/commands/keychain-io/trustable-ai/daily-standup"><img src="https://agentmods.dev/badge/commands/keychain-io/trustable-ai/daily-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/commands/keychain-io/trustable-ai/daily-standup"><img src="https://agentmods.dev/badge/commands/keychain-io/trustable-ai/daily-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 | $0.00000 | $0.03565 |
| Opus 5 | $0.00000 | $0.01783 |
| Sonnet 5 | $0.00000 | $0.00713 |
| Haiku 4.5 | $0.00000 | $0.00357 |
Grade A, and why
daily-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 8d 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 — 436 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Daily Standup Report Workflow
Project: trusted-ai-development-workbench Workflow: Daily Standup Report Purpose: Generate automated daily standup reports for the active sprint
Output Formatting Requirements
IMPORTANT: When generating reports, use actual Unicode emojis, NOT GitHub-style shortcodes:
- ✅ Correct:
⚠️ Warningorℹ️ Info - ❌ Incorrect:
:warning:or:information_source:
Status indicators to use:
- ✅ Completed / On track
- ⚠️ Warning / Below target
- ❌ Critical / Blocked
- ℹ️ Information
- 🔴 High priority
- 🟡 Medium priority
- 🟢 Low priority / Good
Overview
This lightweight workflow generates daily standup reports showing what was completed yesterday, what's planned for today, and any blockers. Perfect for distributed teams or async standups.
Prerequisites
- Active sprint in azure-devops
- Work items with recent activity
Initialize Work Tracking
# Initialize work tracking adapter (auto-selects Azure DevOps or file-based)
import sys
sys.path.insert(0, ".claude/skills")
from work_tracking import get_adapter
from workflows.utilities import (
analyze_sprint,
verify_work_item_states,
get_recent_activity,
identify_blockers
)
from datetime import datetime, timedelta
adapter = get_adapter()
print(f"📋 Work Tracking: {adapter.platform}")
# Get current sprint name (replace CURRENT_SPRINT with actual sprint)
current_sprint = "Sprint 1" # Update this
Workflow Steps
Step 1: Gather Yesterday's Activity
- Query completed work (last 24 hours):
# Use workflow utility to get recent activity activity_result = get_recent_activity(adapter, current_sprint, hours=24) recent_items = activity_result['recent_items'] print(f"Found {activity_result['recent_count']} items updated since yesterday") print(f"Total items in sprint: {activity_result['total_items']}") for item in recent_items: print(f" WI-{item['id']}: {item['title']} [{item['state']}]") # Check for errors if activity_result['errors']: print(f"⚠️ Errors during activity query:") for error in activity_result['errors']: print(f" - {error}")
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.
- 8d ago First seen · 436 lines · 0 tokens per session scan A 391c772ac1c3
daily-standup is a command published in the GitHub repository keychain-io/trustable-ai (2 stars, last pushed 7mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,565 tokens. 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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