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.
git clone --depth 1 https://github.com/Amey-Thakur/AI-SKILLSWrote 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/amey-thakur/ai-skills/qbr-outline)<a href="https://agentmods.dev/commands/amey-thakur/ai-skills/qbr-outline"><img src="https://agentmods.dev/badge/commands/amey-thakur/ai-skills/qbr-outline/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/amey-thakur/ai-skills/qbr-outline"><img src="https://agentmods.dev/badge/commands/amey-thakur/ai-skills/qbr-outline.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 | $0.00017 | $0.00222 |
| Opus 5 | $0.00009 | $0.00111 |
| Sonnet 5 | $0.00003 | $0.00044 |
| Haiku 4.5 | $0.00002 | $0.00022 |
Grade A, and why
qbr-outline 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 6d 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.
What it actually says
You were invoked as a slash command. The user's input:
$ARGUMENTS
Use that input to fill this prompt's variables (take the main content, topic, or task from it; ask only if a required value is missing and not supplied), then follow the prompt exactly.
Outline a quarterly review for:
{period}
Audience: {audience}
Use agent-board-reporting, agent-strategy-review, and project-status-reporting.
Structure:
- Outcomes against the goals set, including misses.
- Metrics with movement and cause.
- What was learned that changes the plan.
- Decisions needed, with options and a recommendation.
- Next quarter's priorities and what is being dropped.
- Risks that need attention above this team.
Rules: lead with outcomes rather than activity. State misses as plainly as wins. Every decision needs options and a recommendation, not an open question. Keep the review short enough that the decisions get time.
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.
- 6d ago First seen · 36 lines · 17 tokens per session scan A 34b986a206ba
qbr-outline is a command published in the GitHub repository Amey-Thakur/AI-SKILLS (7 stars, last pushed 7d ago), licensed MIT. It adds 17 tokens to every session and 222 once invoked, about $0.0001 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 2026-09-06.
Other commands, from other repositories
close
They operate it without you.
create-ticket
Create a work-item ticket (GitHub issue / Jira) from an existing requirements.md, then promote its draft spec folder to docs/specs/ /.
finish-tasks
Finalize a work item after all tasks are done — cleanup (currently closing the ticket) and mark the work complete.
work-status
Report the current status of a work item by reading its spec files (requirements/design/tasks) and execution log. Read-only.
/opsx-apply
Implement tasks from an OpenSpec change (Experimental).
align
Align cross-functional stakeholders.