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/MachineWisdomAI/fava-trailsWrote 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/machinewisdomai/fava-trails/overview)<a href="https://agentmods.dev/commands/machinewisdomai/fava-trails/overview"><img src="https://agentmods.dev/badge/commands/machinewisdomai/fava-trails/overview/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/machinewisdomai/fava-trails/overview"><img src="https://agentmods.dev/badge/commands/machinewisdomai/fava-trails/overview.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 | $0.00671 |
| Opus 5.5 | $0.00000 | $0.00268 |
| Sonnet 5.5 | $0.00000 | $0.00134 |
| Haiku 4.5 | $0.00000 | $0.00067 |
Grade A, and why
overview 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codev CLI Command Reference
Codev provides three CLI tools for AI-assisted software development:
| Tool | Description |
|---|---|
codev |
Project setup, maintenance, and framework commands |
af |
Agent Farm - multi-agent orchestration for development |
consult |
AI consultation with external models (Gemini, Codex, Claude) |
Quick Start
# Create a new project
codev init my-project
# Or add codev to an existing project
codev adopt
# Check your environment
codev doctor
# Start the workspace
af workspace start
# Consult an AI model about a spec
consult -m gemini --protocol spir --type spec
Installation
npm install -g @cluesmith/codev
This installs all three commands globally: codev, af, and consult.
Command Summaries
codev - Project Management
| Command | Description |
|---|---|
codev init [name] |
Create a new codev project |
codev adopt |
Add codev to an existing project |
codev doctor |
Check system dependencies |
codev update |
Update codev templates and protocols |
codev import <source> |
AI-assisted protocol import from other projects |
See codev.md for full documentation.
af - Agent Farm
| Command | Description |
|---|---|
af workspace start |
Start the workspace |
af workspace stop |
Stop all agent farm processes |
af spawn |
Spawn a new builder |
af status |
Show status of all agents |
af cleanup |
Clean up a builder worktree |
af send |
Send instructions to a builder |
af open |
Open file annotation viewer |
af shell |
Spawn a utility shell |
af tower |
Cross-project dashboard |
See agent-farm.md for full documentation.
consult - AI Consultation
| Command | Description |
|---|---|
consult -m <model> --prompt "text" |
General consultation |
consult -m <model> --protocol spir --type spec |
Protocol-based review |
consult stats |
View consultation statistics |
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 · 97 lines · 0 tokens per session scan A 4847485250a4
overview is a command published in the GitHub repository MachineWisdomAI/fava-trails (26 stars, last pushed today), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 671 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 2026-08-30.
Other commands, from other repositories
sugar-review
Review and manage pending Sugar tasks interactively.
sugar-task
Create a comprehensive Sugar task with rich context and metadata.
kibi-signoff
Show the Kibi requirements signoff view for the current change, or the decisions waiting for the person.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.