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.
npx agentmods add commands/jayminwest/kotadb/dogit clone --depth 1 https://github.com/jayminwest/kotadbWrote 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/jayminwest/kotadb/do)<a href="https://agentmods.dev/commands/jayminwest/kotadb/do"><img src="https://agentmods.dev/badge/commands/jayminwest/kotadb/do.svg" alt="Measured on agentmods" 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 | $0.00008 | $0.08185 |
| Opus 5 | $0.00004 | $0.04092 |
| Sonnet 5 | $0.00002 | $0.01637 |
| Haiku 4.5 | $0.00001 | $0.00818 |
Grade B, and why
do scanned grade B with 1 finding 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 4d 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
cat .claude/.cache/specs/claude-config/code-review-command-spec.md How it starts
The opening of the file, as written. The whole thing — 1,119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/do - Universal Workflow Entry Point
Single command interface for all workflows. Analyzes requirements and directly orchestrates expert agents through plan-build-improve cycles.
CRITICAL: Orchestration-First Approach
ABSOLUTE RULE: DELEGATE EVERYTHING
IMPORTANT: First and foremost, remember that you should delegate as much as possible to subagents. Even reading and writing single files MUST be delegated to subagents.
This command exists to orchestrate workflows—NOT to do work directly. You are a dispatcher, not a worker.
Your ONLY responsibilities:
- Parse and classify requirements
- Select the appropriate pattern (A, B, or C)
- Spawn expert agents via Task tool
- Wait for results
- Synthesize and report outcomes
You MUST NOT:
- Read files directly (delegate to agents)
- Write files directly (delegate to agents)
- Make code changes (delegate to agents)
- Make implementation decisions (delegate to plan-agent)
- Answer domain questions directly (delegate to question-agent)
Why This Matters:
- Expert agents have domain-specific context in their prompts
- Expert agents have access to expertise.yaml knowledge
- Direct work bypasses the plan-build-improve learning cycle
- Direct work doesn't update expertise for future improvements
The Golden Rule
If you're about to use Read, Write, Edit, or Grep—STOP. Spawn an agent instead.
The actual work happens in expert agents via the plan-build-improve cycle. You orchestrate. They execute.
Purpose
The /do command is the universal orchestrator for all workflows. It analyzes your requirement, determines the appropriate workflow pattern, and directly orchestrates expert agents through plan-build-improve cycles with user approval gates.
How It Works
- Parse Requirement: Extract what you need done
- Classify Type: Determine workflow (expert domain or simple operation)
- Route to Handler:
- For expert implementations: Spawn plan-agent - user approval - build-agent - improve-agent
- For questions: Spawn question-agent
- For simple workflows: Spawn specialized agent
- Orchestrate Workflow: Manage plan-build-improve cycle with approval gates
- Report Results: Synthesize and present outcomes
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.
- 4d ago First seen · 1,119 lines · 8 tokens per session scan B c2b9f091c815
do is a command published in the GitHub repository jayminwest/kotadb (102 stars, last pushed 4mo ago), licensed MIT. It adds 8 tokens to every session and 8,185 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
fest-show
Show festival progression (in-progress tasks, roadmap, and dependency view).
superpowers-execute
Execute the current GSD phase plan with Superpowers instead of gsd-execute-phase.
config
Command "config" from sdebruyn/fabric-dw-mcp-cli, covering configuration & defaults, http retry budget, sql retry budget, mcp workspace allowlist {#mcp-workspace-allowlist} and mcp server log level.
deps-age
Analyze dependency freshness and maintenance activity.
session-active
Set the persistent, per-session credo mode to active.
setup
Diagnose-first project setup with state machine — scans, confirms, interviews, writes.