Borrowing it
Nothing to install: this file belongs to d-o-hub/github-template-ai-agents. 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/d-o-hub/github-template-ai-agents/main/.gemini/commands/adr.tomlgit clone --depth 1 https://github.com/d-o-hub/github-template-ai-agentsWrote 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/d-o-hub/github-template-ai-agents/adr)<a href="https://agentmods.dev/commands/d-o-hub/github-template-ai-agents/adr"><img src="https://agentmods.dev/badge/commands/d-o-hub/github-template-ai-agents/adr/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/d-o-hub/github-template-ai-agents/adr"><img src="https://agentmods.dev/badge/commands/d-o-hub/github-template-ai-agents/adr.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 | $0.00155 |
| Opus 5.5 | $0.00000 | $0.00062 |
| Sonnet 5.5 | $0.00000 | $0.00031 |
| Haiku 4.5 | $0.00000 | $0.00015 |
Grade A, and why
adr 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 18d 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
description = "Start ADR-driven development — perform TRIZ analysis and write an Architecture Decision Record (ADR) before planning tasks via GOAP" prompt = """ Invoke the adr-driven-development approach. Begin by understanding what the user wants to build. Execute Phase 1 (ANALYZE & STRATEGIZE):
- Ask clarifying questions about the objective, constraints, and architecture.
- Use TRIZ concepts (the triz-solver skill) to evaluate the problem and resolve architectural contradictions.
- Draft an Architecture Decision Record (ADR) detailing the Context, Decision, and Consequences.
Save the ADR in the
plans/directory and confirm with the user before proceeding to Phase 2 (DECOMPOSE & PLAN) via the goap-agent. """
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.
- 18d ago Changed 383db1afdc5e
- 1mo ago First seen · 10 lines · 0 tokens per session scan A 85ed49b4a109
adr is a command published in the GitHub repository d-o-hub/github-template-ai-agents (2 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 155 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 2026-09-03.
Other commands, from other repositories
fest-show
Show festival progression (in-progress tasks, roadmap, and dependency view).
synthesise-reviews
Deduplicate and reconcile multiple completed review reports into one prioritised revision plan with conflicts and dependencies made explicit. Use when parallel reviewers have returned findings that need a single action sequence. Not for running the reviews; use $review-cluster.
verify-math
Verify a self-authored mathematical result end to end by routing claims across adversarial review, numerical falsification, symbolic or CAS checks, and Lean, then aggregating one report. Use when a theorem, proposition, conjecture, or paper-wide mathematical argument needs the appropriate combination of verification…
firebase-publish
Create or reuse a Firebase project, configure Hosting, and deploy the current static site. Never deletes.
tdd-feature
Implement a new feature using full TDD loop.
auditoria-legal
Grupo: Trabajo con el framework En una frase: Auditoría de cumplimiento legal del producto — territorio, evidencia y lo que el código no cubre. Cuándo: Antes de publicar una app o web: registro, cookies, analítica, emails, suscripciones, contenido de usuarios. Quién: Cualquier operador del repo.