Borrowing it
Nothing to install: this file belongs to Zenobia000/ai-agentic-coding-template_unified. 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/Zenobia000/ai-agentic-coding-template_unified/main/.ai/commands/template-integration.mdgit clone --depth 1 https://github.com/Zenobia000/ai-agentic-coding-template_unifiedWrote 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/zenobia000/ai-agentic-coding-template_unified/template-integration)<a href="https://agentmods.dev/commands/zenobia000/ai-agentic-coding-template_unified/template-integration"><img src="https://agentmods.dev/badge/commands/zenobia000/ai-agentic-coding-template_unified/template-integration/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/zenobia000/ai-agentic-coding-template_unified/template-integration"><img src="https://agentmods.dev/badge/commands/zenobia000/ai-agentic-coding-template_unified/template-integration.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 | $0.00774 |
| Opus 5.5 | $0.00000 | $0.00310 |
| Sonnet 5.5 | $0.00000 | $0.00155 |
| Haiku 4.5 | $0.00000 | $0.00077 |
Grade A, and why
template-integration 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- template-integration — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Template Integration Guide
Overview
This guide ensures all workflow commands use standardized templates and automatically save outputs to memory-bank.
Command Template Mappings
1. /van - Requirements Analysis
Templates Used:
.ai/template/outputs/van/requirements-spec.mdOutput Location:memory-bank/requirements/requirements-[timestamp].mdmemory-bank/activeContext.md(overwrite)
2. /plan - Conceptual Design
Templates Used:
.ai/template/outputs/plan/tasks.mdOutput Location:memory-bank/tasks.md(overwrite)memory-bank/planning/wbs-[epic].md
3. /adr - Tech Selection
Templates Used:
.ai/template/outputs/adr/adr-template.mdOutput Location:memory-bank/decisions/adr-[number]-[slug].mdmemory-bank/decisions/registry.yaml(update)
4. /creative - Architecture Design
Templates Used:
.ai/template/outputs/creative/architecture-design.mdOutput Location:memory-bank/designs/architecture/architecture-[version].mdmemory-bank/techContext.md(overwrite)
5. /design-validator - Detail Design & Validation
Templates Used:
.ai/template/outputs/design-validator/validation-report.md.ai/template/outputs/design-validator/openapi-spec.yamlOutput Location:memory-bank/validation/report-[timestamp].mdmemory-bank/designs/api/openapi-[version].yaml
6. /implement - Implementation
Templates Used:
.ai/template/outputs/implement/implementation-guide.mdOutput Location:memory-bank/implementation/guide-[version].md
7. /reflect - Evolution & Optimization
Templates Used:
.ai/template/outputs/reflect/progress-report.mdOutput Location:memory-bank/progress.md(overwrite)memory-bank/metrics/dashboard.json(overwrite)
AI Tool Instructions
When executing any workflow command, follow these steps:
- Load Template: Read the corresponding template from
.ai/template/outputs/[command]/ - Gather Data: Collect required information from context and user input
- Fill Template: Replace all
{{variables}}with actual values - Save to Memory Bank: Write output to specified location in
memory-bank/ - Confirm: Report successful generation and file location
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 · 94 lines · 0 tokens per session scan A 840180eb0637
template-integration is a command published in the GitHub repository Zenobia000/ai-agentic-coding-template_unified (7 stars, last pushed 9mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 774 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.
Other commands, from other repositories
minutes-ideas
Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.
learn
Force claude-smart to extract learnings from this session now.
memory-store
Store an insight, decision, or pattern to memory.
analyze-context
USE WHEN you want to analyze project context before starting work on a task. Calls context + recall, then synthesizes goals, decisions, gotchas, and relevant memories into a pre-task brief.
cc-memory
Configure persistent memory that survives across sessions using a layered approach: split rule files for always-loaded context, auto-memory for organic learning, and optional MCP-backed long-term memory for large codebases.
lians-recall
Recall current (non-stale) facts from Lians memory, optionally as-of a past date.