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/sprint-review.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/sprint-review)<a href="https://agentmods.dev/commands/keychain-io/trustable-ai/sprint-review"><img src="https://agentmods.dev/badge/commands/keychain-io/trustable-ai/sprint-review/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/sprint-review"><img src="https://agentmods.dev/badge/commands/keychain-io/trustable-ai/sprint-review.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 | $0.14180 |
| Opus 5 | $0.00000 | $0.07090 |
| Sonnet 5 | $0.00000 | $0.02836 |
| Haiku 4.5 | $0.00000 | $0.01418 |
Grade A, and why
sprint-review 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 9d 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 — 1,743 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sprint Review Workflow
Project: trusted-ai-development-workbench Workflow: Sprint Review (Acceptance & Deployment Readiness) Purpose: Review sprint completion, run acceptance tests, assess deployment readiness, and close sprint
Output Formatting Requirements
IMPORTANT: Use actual Unicode emojis in reports, NOT GitHub-style shortcodes.
Workflow Overview
┌─────────────────────────────────────────────────────────────────────────────┐
│ SPRINT REVIEW - Acceptance & Deployment Readiness │
│ │
│ Step 1: Collect sprint completion metrics │
│ Step 1.5: Identify EPICs for testing │
│ Step 1.6: Retrieve test plans from work items │
│ Step 1.7: Execute tests and generate reports │
│ Step 1.8: Attach test reports to EPIC work items │
│ Step 1.9: Auto-mark EPICs Done when all Features Done & tests pass │
│ Step 2: /tester → Run acceptance tests │
│ Step 3: /security-specialist → Final security review │
│ Step 4: /engineer → Deployment readiness assessment │
│ Step 5: /scrum-master → Sprint closure decision │
│ Step 6: Human approval → Close sprint or extend │
│ │
│ Each agent command spawns a FRESH CONTEXT WINDOW via Task tool │
└─────────────────────────────────────────────────────────────────────────────┘
Initialize Workflow
# Initialize work tracking adapter
import sys
from datetime import datetime
sys.path.insert(0, ".claude/skills")
from work_tracking import get_adapter
adapter = get_adapter()
print(f"📋 Work Tracking: {adapter.platform}")
sprint_name = input("Sprint name (e.g., Sprint 3): ")
# Load sprint work items
try:
sprint_items = adapter.query_work_items(
filters={
'System.IterationPath': f'Trusted AI Development Workbench\\{sprint_name}'
}
)
print(f"📋 Found {len(sprint_items)} items in {sprint_name}")
except Exception as e:
print(f"❌ Failed to load sprint items: {e}")
sprint_items = []
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.
- 9d ago First seen · 1,743 lines · 0 tokens per session scan A 7c5fab4d287d
sprint-review 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 14,180 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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