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/hainamchung/agent-assistant/autogit clone --depth 1 https://github.com/hainamchung/agent-assistantWrote 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/hainamchung/agent-assistant/auto)<a href="https://agentmods.dev/commands/hainamchung/agent-assistant/auto"><img src="https://agentmods.dev/badge/commands/hainamchung/agent-assistant/auto.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 | $0.00736 |
| Opus 5 | $0.00004 | $0.00368 |
| Sonnet 5 | $0.00002 | $0.00147 |
| Haiku 4.5 | $0.00001 | $0.00074 |
Grade A, and why
auto 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 yesterday.
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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/auto — Autonomous Workflow Orchestrator
ROUTER DIRECTIVE: Analyze task and autonomously execute complete workflow without user intervention between phases.
$ARGUMENTS
🛑 PRE-FLIGHT (DO FIRST — BLOCKS EXECUTION)
LOAD now (in order; path ./rules/ or ~/.{TOOL}/skills/agent-assistant/rules/):
- CORE.md — Identity, Laws, Routing
- PHASES.md — Phase Execution
- AGENTS.md — Tiered Execution
⛔ Do not run any workflow phase until all are loaded. Follow all rules in those files. Then run this file's ROUTING LOGIC, LOAD the chosen variant workflow, and execute it.
ROUTING LOGIC
1. Analyze task type
2. Determine optimal workflow
3. Execute all phases autonomously
4. Report only final result
⛔ INCREMENTAL EXECUTION (MANDATORY)
One phase at a time, each phase independent: Phase 1 → then Phase 2 → … in one reply. No batching (load only what each phase needs). Within each phase: when doing a part, output it in format so user sees what’s happening (announce before doing).
🎭 Phase 1: TASK ANALYSIS
| Attribute | Value |
|---|---|
| Agent | tech-lead |
| Goal | Classify task and select workflow |
⚡ ADAPTIVE EXECUTION
IF platform supports subagents:
Delegate to
tech-leadsubagent. Do NOT read agent file directly.
ELSE (EMBODY fallback):
Load
{AGENTS_PATH}/tech-lead.mdEMBODY [tech-lead] — Apply methodology from agent file.
Exit Criteria:
- Task type identified
- Workflow selected
- Execution plan created
🎭 Phase 2: AUTONOMOUS EXECUTION
Execute selected workflow phases without pause:
| Task Type | Workflow |
|---|---|
| Bug/Error | /debug:fast or /debug:hard |
| New Feature | /code:hard |
| Question | /ask:fast or /ask:hard |
| Planning | /plan:fast or /plan:hard |
| Testing | /test:fast or /test:hard |
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.
- yesterday First seen · 112 lines · 8 tokens per session scan A edec22db2505
auto is a command published in the GitHub repository hainamchung/agent-assistant (54 stars, last pushed 3mo ago), licensed MIT. It adds 8 tokens to every session and 736 once invoked, about $0.0000 per session on Opus 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 2026-09-03.
Other commands, from other repositories
create-command
Create a new obsidian-second-brain command via interview - zero markdown editing required.
obsidian-health
Run a vault health check - grouped by severity, detects contradictions, concept gaps, stale claims, and structural issues.
obsidian-visualize
Generate a visual canvas map of your vault - see the shape of your second brain and how knowledge connects.
obsidian-architect
Scan a codebase and write a maintained set of architecture notes into the vault - overview, per-module notes, key decisions. Re-run to refresh without clobbering your edits.
obsidian-export
Export a clean structured snapshot of the vault that any agent or tool can consume - flat JSON, markdown index, or an OKF (Open Knowledge Format) bundle.
obsidian-retrieval-eval
Measure how well vault search finds the right note for a natural-language question - recall@k and MRR, with the concrete failures.