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/jayvee/aigonWrote 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/jayvee/aigon/ard)<a href="https://agentmods.dev/commands/jayvee/aigon/ard"><img src="https://agentmods.dev/badge/commands/jayvee/aigon/ard.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 5.1 | $0.00015 | $0.01452 |
| Opus 5 | $0.00008 | $0.00726 |
| Sonnet 5 | $0.00003 | $0.00290 |
| Haiku 4.5 | $0.00002 | $0.00145 |
Grade A, and why
ard 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 3d 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.
This is a copy
100% identical to research-do — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
aigon-research-do
Run this command followed by the Research ID.
aigon research-do {{args}}
Argument Resolution
If no ID is provided, or the ID doesn't match an existing topic in progress:
- List all files in
./docs/specs/research-topics/03-in-progress/matchingresearch-*.md - If a partial ID or name was given, filter to matches
- Present the matching topics and ask the user to choose one
This command is the research equivalent of feature-do: it is the main work step after research-start.
Step 0: Verify your workspace (MANDATORY)
Before doing ANYTHING else, verify your environment:
pwd
git branch --show-current
Research agents work in the main repository on the current branch. This is normal — research does not require branch isolation because you are only writing findings files, not modifying code.
CRITICAL RULES for research:
- You MUST NOT modify any source code files (
.js,.ts,.py,.json, etc.) - You MUST NOT modify other agents' findings files
- You MUST ONLY write to YOUR findings file:
docs/specs/research-topics/logs/research-{ID}-cc-findings.md - You MUST NOT run
git checkout,git branch, or create new branches — stay where you are
Required Lifecycle Step
Before starting active research, run:
aigon agent-status implementing
This updates your agent state in the main repo so the dashboard and coordinator know you're actively working.
Your Task
-
Find the research topic in
docs/specs/research-topics/03-in-progress/research-{ID}-*.md -
Check for worktree/Fleet mode: Look for your findings file at:
docs/specs/research-topics/logs/research-{ID}-cc-findings.md -
Conduct deep research to answer each question in the research doc. Go broad before going deep:
How to research thoroughly:
- Search the web for documentation, blog posts, comparisons, and real-world usage. Don't rely only on what's in the codebase.
- Read primary sources — official docs, GitHub repos, RFCs — not just summaries.
- Explore multiple approaches before settling on one. For each question, consider at least 2-3 alternatives.
- Look at the codebase to understand current patterns, constraints, and what's already been tried.
- Compare trade-offs with evidence, not just intuition. Include concrete pros/cons.
- Cite your sources — every claim should link back to where you found it.
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.
- 3d ago First seen · 135 lines · 15 tokens per session scan A 23cb162ad8f5
ard is a command published in the GitHub repository jayvee/aigon (25 stars, last pushed 6d ago), licensed Apache-2.0. It adds 15 tokens to every session and 1,452 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to research-do, differing in 2 lines, and is treated as a copy.
Other commands, from other repositories
pick-agent
A command that helps users choose and import only the agent role they need, such as a frontend developer, researcher, or editor.
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.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.