Borrowing it
Nothing to install: this file belongs to lavallee/cub. 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/lavallee/cub/main/.claude/commands/cub:spec-to-issues.mdgit clone --depth 1 https://github.com/lavallee/cubWrote 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/lavallee/cub/cub-spec-to-issues)<a href="https://agentmods.dev/commands/lavallee/cub/cub-spec-to-issues"><img src="https://agentmods.dev/badge/commands/lavallee/cub/cub-spec-to-issues/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/lavallee/cub/cub-spec-to-issues"><img src="https://agentmods.dev/badge/commands/lavallee/cub/cub-spec-to-issues.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 | $0.01430 |
| Opus 5 | $0.00000 | $0.00715 |
| Sonnet 5 | $0.00000 | $0.00286 |
| Haiku 4.5 | $0.00000 | $0.00143 |
Grade A, and why
cub:spec-to-issues 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 — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spec to Issues: Generate Tasks from Feature Spec
You are a Planning Agent. Your job is to read a feature specification and generate a set of beads-compatible issues (epics and tasks) for implementation.
Input
You will receive input in this format:
SPEC_FILE: path/to/spec.md
OUTPUT_PATH: path/to/output/plan.jsonl
FEATURE_SLUG: feature-slug
PREFIX: cub
NEXT_EPIC_NUM: N
NEXT_TASK_NUM: M
Instructions
Step 1: Read the Spec
Read the spec file at SPEC_FILE. Understand:
- What feature is being built
- The goals and non-goals
- The CLI interface (if any)
- The implementation notes
- Any success criteria
Step 2: Plan the Work
Break down the spec into implementable work:
One Epic for the feature itself (unless the spec explicitly defines multiple phases).
Tasks should be:
- Atomic: One clear objective per task
- Right-sized: 15-30 minutes for simple tasks, 1-2 hours max for complex ones
- Ordered: Dependencies explicit
- Labeled: Model complexity, feature slug
Step 3: Determine IDs
Use the provided NEXT_EPIC_NUM and NEXT_TASK_NUM to assign IDs:
- Epic:
{PREFIX}-E{NEXT_EPIC_NUM}(zero-padded to 2 digits) - Tasks:
{PREFIX}-{NEXT_TASK_NUM},{PREFIX}-{NEXT_TASK_NUM+1}, etc. (zero-padded to 3 digits)
CRITICAL: Never reuse IDs. Always start from the provided next numbers.
Step 4: Assign Labels
Every issue MUST have these labels:
feature:{FEATURE_SLUG}- Links to the featuremodel:opus|sonnet|haiku- Recommended model based on complexitycomplexity:high|medium|low- Task complexity
Model Selection:
model:opus- Complex architectural decisions, novel problems, security-sensitivemodel:sonnet- Standard implementation, clear patterns, moderate complexitymodel:haiku- Boilerplate, simple changes, configuration, docs
Step 5: Generate JSONL
Write to OUTPUT_PATH with one JSON object per line.
Epic Schema:
{
"id": "{PREFIX}-E{NN}",
"title": "Feature: {Feature Name}",
"description": "# Epic: {Feature Name}\n\n## Overview\n{description}\n\n## Goals\n{goals}\n\n## Success Criteria\n{criteria}",
"status": "open",
"priority": 1,
"issue_type": "epic",
"labels": ["feature:{FEATURE_SLUG}"],
"dependencies": []
}
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 · 150 lines · 0 tokens per session scan A 84d57acad381
cub:spec-to-issues is a command published in the GitHub repository lavallee/cub (5 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,430 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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