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/nguyenvanduocit/research-kit/definegit clone --depth 1 https://github.com/nguyenvanduocit/research-kitWhat 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 | $0.00014 | $0.01507 |
| Opus 5 | $0.00007 | $0.00754 |
| Sonnet 5 | $0.00003 | $0.00301 |
| Haiku 4.5 | $0.00001 | $0.00151 |
Grade A, and why
define 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.
How it starts
The opening of the file, as written. The whole thing — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
User Input
$ARGUMENTS
You MUST consider the user input before proceeding (if not empty).
Outline
The text the user typed after /research.define in the triggering message is the research topic description. Assume you always have it available in this conversation even if {ARGS} appears literally below. Do not ask the user to repeat it unless they provided an empty command.
Given that research topic description, do this:
-
Generate a concise short name (2-4 words) for the branch:
- Analyze the research description and extract the most meaningful keywords
- Create a 2-4 word short name that captures the essence of the research
- Use descriptive format (e.g., "ai-market-analysis", "blockchain-security")
- Preserve technical terms and acronyms (AI, ML, IoT, etc.)
- Keep it concise but descriptive enough to understand the research at a glance
- Examples:
- "I want to research AI market trends in healthcare" → "ai-healthcare-trends"
- "Analyze blockchain security vulnerabilities" → "blockchain-security"
- "Study remote work productivity impact" → "remote-work-productivity"
-
Check for existing branches before creating new one:
a. First, fetch all remote branches to ensure we have the latest information:
git fetch --all --pruneb. Find the highest research number across all sources for the short-name:
- Remote branches:
git ls-remote --heads origin | grep -E 'refs/heads/[0-9]+-<short-name>$' - Local branches:
git branch | grep -E '^[* ]*[0-9]+-<short-name>$' - Research directories: Check for directories matching
research/[0-9]+-<short-name>
c. Determine the next available number:
- Extract all numbers from all three sources
- Find the highest number N
- Use N+1 for the new branch number
d. Run the script
{SCRIPT}with the calculated number and short-name:- Pass
--number N+1and--short-name "your-short-name"along with the research description - Example:
{SCRIPT} --json --number 5 --short-name "ai-healthcare" "Research AI trends in healthcare"
- Remote branches:
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 · 143 lines · 14 tokens per session scan A afdc89507b1e
define is a command published in the GitHub repository nguyenvanduocit/research-kit (20 stars, last pushed 5mo ago), licensed MIT. It adds 14 tokens to every session and 1,507 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It comes from a forked repository.
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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.