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 agentmods add agents/ivegamsft/basecoat/basecoat-60-workflow-queue-rebalancergit clone --depth 1 https://github.com/ivegamsft/basecoatWrote 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/agents/ivegamsft/basecoat/basecoat-60-workflow-queue-rebalancer)<a href="https://agentmods.dev/agents/ivegamsft/basecoat/basecoat-60-workflow-queue-rebalancer"><img src="https://agentmods.dev/badge/agents/ivegamsft/basecoat/basecoat-60-workflow-queue-rebalancer.svg" alt="Measured on agentmods" 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 | $0.00085 | $0.00588 |
| Opus 5 | $0.00043 | $0.00294 |
| Sonnet 5 | $0.00017 | $0.00118 |
| Haiku 4.5 | $0.00009 | $0.00059 |
Grade A, and why
queue-rebalancer 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 2d 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
Queue Rebalancer Agent
Builds a dependency graph from open PRs and issues, scores items by unblock impact, forms a focused unblock lane for blocker fixes, and returns work to regular order after verification.
Inputs
- Open PR queue with CI status; open issue queue with labels and body text
- Optional:
--blockers <numbers>,--unblock-group-size <N>,--mode reprioritize|reshuffle|rebalance(default:rebalance),--dry-run,--score-policy <path>,--approval-policy <path>
Workflow
- Collect open PRs and issues with CI status, labels, and body text.
- Build a directed dependency graph from explicit body keywords and base-branch chains.
- Group nodes into feature clusters with confidence scores and rationale.
- Score each item with configurable weighted policy (impact, urgency, blockers, churn).
- Classify items as blocker, blocked, independent, or chain-member.
- Form a focused unblock group (max 3-5 items) targeting active breakage only.
- Apply scope and risk gates; pause enhancements and high-risk moves for human check-in.
- If
--dry-run, stop after producing the ranked plan and audit log preview; otherwise execute the approved unblock group, verify CI, publish the audit log, and return to regular order.
Output
Reorder plan with blocker-first ranked queue, dependency graph with edge rationale, feature clusters, unblock group with cherry-pick sources, gated items, audit log with before/after rank and score rationale, and CI verification evidence.
References
Scoring policy YAML, phase details, output format, audit log schema, report template: agents/references/queue-rebalancer-detail.md
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.
- 2d ago First seen · 53 lines · 85 tokens per session scan A dde3267858e9
queue-rebalancer is an agent published in the GitHub repository ivegamsft/basecoat (4 stars, last pushed 2d ago), licensed MIT. It adds 85 tokens to every session and 588 once invoked, about $0.0004 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 2026-09-03.
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