Borrowing it
Nothing to install: this file belongs to NguyenSiTrung/Conductor-Beads. 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/NguyenSiTrung/Conductor-Beads/main/.claude/skills/beads/commands/template.mdgit clone --depth 1 https://github.com/NguyenSiTrung/Conductor-BeadsWrote 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/nguyensitrung/conductor-beads/template)<a href="https://agentmods.dev/commands/nguyensitrung/conductor-beads/template"><img src="https://agentmods.dev/badge/commands/nguyensitrung/conductor-beads/template/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/nguyensitrung/conductor-beads/template"><img src="https://agentmods.dev/badge/commands/nguyensitrung/conductor-beads/template.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 | $0.01663 |
| Opus 5.5 | $0.00000 | $0.00665 |
| Sonnet 5.5 | $0.00000 | $0.00333 |
| Haiku 4.5 | $0.00000 | $0.00166 |
Grade A, and why
template 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 1mo 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.
This is a copy
100% identical to template — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 338 lines — stays where its author put it; the contents beside it link to each section on GitHub.
bd template
Manage issue templates for streamlined issue creation.
Synopsis
Templates provide pre-filled structures for common issue types, making it faster to create well-formed issues with consistent formatting.
bd template list
bd template show <template-name>
bd template create <template-name>
Description
Templates can be:
- Built-in: Provided by bd (epic, bug, feature)
- Custom: Stored in
.beads/templates/directory
Each template defines default values for:
- Description structure with placeholders
- Issue type (bug, feature, task, epic, chore)
- Priority (0-4)
- Labels
- Design notes structure
- Acceptance criteria structure
Commands
list
List all available templates (built-in and custom).
bd template list
bd template list --json
Examples:
$ bd template list
Built-in Templates:
epic
Type: epic, Priority: P1
Labels: epic
bug
Type: bug, Priority: P1
Labels: bug
feature
Type: feature, Priority: P2
Labels: feature
show
Show detailed structure of a specific template.
bd template show <template-name>
bd template show <template-name> --json
Examples:
$ bd template show bug
Template: bug
Type: bug
Priority: P1
Labels: bug
Description:
## Summary
[Brief description of the bug]
## Steps to Reproduce
...
create
Create a custom template in .beads/templates/ directory.
bd template create <template-name>
This creates a YAML file with default structure that you can edit to customize.
Examples:
$ bd template create performance
✓ Created template: .beads/templates/performance.yaml
Edit the file to customize your template.
$ cat .beads/templates/performance.yaml
name: performance
description: |-
[Describe the issue]
## Additional Context
[Add relevant details]
type: task
priority: 2
labels: []
design: '[Design notes]'
acceptance_criteria: |-
- [ ] Acceptance criterion 1
- [ ] Acceptance criterion 2
# Edit the template to customize it
$ vim .beads/templates/performance.yaml
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.
- 1mo ago First seen · 338 lines · 0 tokens per session scan A dd8865a9556a
template is a command published in the GitHub repository NguyenSiTrung/Conductor-Beads (23 stars, last pushed 7mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,663 tokens. A static security scan graded it A with 0 findings. It is 100% identical to template, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
template
Manage issue templates for streamlined issue creation.
add-note
Add an internal or external note to a ConnectWise PSA ticket.
fest-show
Show festival progression (in-progress tasks, roadmap, and dependency view).
sync-linear
Sync current work with Linear ticket status.
dispatcher
Use when you want the orchestrator to pick the next repo to work on across your whole portfolio — it enumerates candidate repos below the confinement root, resolves free/busy from each repo's session.lock lease, ranks the FREE ones by backlog priority × staleness × readiness, recommends the single most worthwhile one…
workpm
A project-management workflow for coordinating multiple AI workers through five stages. It includes task assignment, shared activity logs, worker replacement, and final checks.