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.
git clone --depth 1 https://github.com/ruslan-korneev/claude-pluginsWrote 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/ruslan-korneev/claude-plugins/adr)<a href="https://agentmods.dev/commands/ruslan-korneev/claude-plugins/adr"><img src="https://agentmods.dev/badge/commands/ruslan-korneev/claude-plugins/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/ruslan-korneev/claude-plugins/adr"><img src="https://agentmods.dev/badge/commands/ruslan-korneev/claude-plugins/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 | $0.00009 | $0.01126 |
| Opus 5.5 | $0.00004 | $0.00450 |
| Sonnet 5.5 | $0.00002 | $0.00225 |
| Haiku 4.5 | $0.00001 | $0.00113 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 256 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Command /architect:adr
Create an Architecture Decision Record (ADR) to document significant architectural decisions.
Instructions
Step 1: Check Existing ADRs
Find existing ADRs to determine the next number:
Glob: docs/adr/*.md, **/adr/*.md, ADR-*.md
Step 2: Gather Context
Use AskUserQuestion to understand the decision:
Questions:
- What problem are you solving?
- What constraints do you have? (tech stack, team expertise, timeline)
- What alternatives did you consider?
- What are the expected benefits?
- What are the potential risks?
Step 3: Create ADR Directory (if needed)
mkdir -p docs/adr
Step 4: Generate ADR
Create file: docs/adr/{{ next_number }}-{{ title | slugify }}.md
# ADR-{{ number }}: {{ title }}
## Status
Proposed
## Date
{{ today }}
## Context
{{ context }}
### Problem Statement
{{ problem }}
### Constraints
- {{ constraint_1 }}
- {{ constraint_2 }}
- {{ constraint_3 }}
### Requirements
- {{ requirement_1 }}
- {{ requirement_2 }}
## Decision
{{ decision }}
### Key Points
1. {{ key_point_1 }}
2. {{ key_point_2 }}
3. {{ key_point_3 }}
### Implementation Details
{{ implementation_details }}
## Consequences
### Positive
- {{ positive_1 }}
- {{ positive_2 }}
- {{ positive_3 }}
### Negative
- {{ negative_1 }}
- {{ negative_2 }}
### Risks
| Risk | Likelihood | Impact | Mitigation |
|------|------------|--------|------------|
| {{ risk_1 }} | {{ likelihood }} | {{ impact }} | {{ mitigation }} |
| {{ risk_2 }} | {{ likelihood }} | {{ impact }} | {{ mitigation }} |
## Alternatives Considered
### {{ alternative_1 }}
{{ description }}
**Pros:**
- {{ pro_1 }}
- {{ pro_2 }}
**Cons:**
- {{ con_1 }}
- {{ con_2 }}
**Rejected because:** {{ rejection_reason }}
### {{ alternative_2 }}
{{ description }}
**Pros:**
- {{ pro_1 }}
**Cons:**
- {{ con_1 }}
**Rejected because:** {{ rejection_reason }}
## References
- {{ reference_1 }}
- {{ reference_2 }}
## Notes
{{ additional_notes }}
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 · 256 lines · 9 tokens per session scan A 26df92324a88
adr is a command published in the GitHub repository ruslan-korneev/claude-plugins (5 stars, last pushed 7mo ago), licensed MIT. It adds 9 tokens to every session and 1,126 once invoked, about $0.0000 per session on Opus 5.5. 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 2026-08-31.
Other commands, from other repositories
guide
Ask the plugin about itself — what a config key does, how the plan gate grades, what the journal can prove — answered from its own docs with a citation for every claim, by the read-only guide agent.
init
A setup command for connecting an existing project to Octopus, a workflow built around OpenSpec project specifications and tracked changes. It checks the required command-line tool and project structure, surveys the codebase, and creates an Arena handover report.
code-review
Perform a code-review.
spec
A requirements-planning command for OpenSpec, a tool that records software changes as proposals, specification updates, and task lists. It clarifies the request, challenges risky assumptions, and pauses for approval before implementation.
debug
A debugging command that sends an error, log, or screenshot to a debugger agent for analysis. The debugger reports confirmed facts separately from possible explanations and does not modify files.
db
A read-only database consultation command covering SQL Server, SQLite, and PostgreSQL, which are systems for storing structured application data.