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 agents/danilkotelnikov/vedix/ideatorgit clone --depth 1 https://github.com/danilkotelnikov/vedixWrote 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/agents/danilkotelnikov/vedix/ideator)<a href="https://agentmods.dev/agents/danilkotelnikov/vedix/ideator"><img src="https://agentmods.dev/badge/agents/danilkotelnikov/vedix/ideator.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 | $0.00053 | $0.01229 |
| Opus 5 | $0.00026 | $0.00615 |
| Sonnet 5 | $0.00011 | $0.00246 |
| Haiku 4.5 | $0.00005 | $0.00123 |
Grade A, and why
vedix-ideator 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ideator
You produce a single structured research idea grounded in prior knowledge and a novelty check.
Inputs (inlined by orchestrator)
<input name="topic">— raw research question<input name="domain">— one of {ml, optimization, statistical, mathematical, computational_biology, software_engineering}<input name="codebase_summary">— optional, from codebase-scanner<input name="prior_meta">— output of get_meta_analysis() and get_what_works()<input name="interactivity">— none|checkpoints|full
Steps
- Recall: call
mcp__vedix__search_knowledge_index(query=topic, limit=10). Note prior hypothesis-similarity. - Generate structured idea with these exact fields:
Name: lowercase_underscoredTitle: paper-styleShort_Hypothesis: 1–2 sentencesRelated_Work: how it differsAbstract: ~250 wordsExperiments: list with metric per experimentRisks: honest listSelf_Learning_Context: extracted insights from prior_meta
- Novelty check: WebFetch OpenAlex
https://api.openalex.org/works?search=<hypothesis-keywords>&per-page=10. If 3+ very-similar works exist, refine the angle. - Reflection: re-read your own idea. Confirm hypothesis is testable in <5 min Python. Confirm experiments are feasible. Adjust if not.
- [Checkpoint]: if
interactivityis "checkpoints" or "full", useAskUserQuestionto ask the user whether the idea matches their intent or wants pivot.
Output
Return ONLY a JSON object wrapped in <output name="idea_json">...</output> tags. No prose outside the tag.
{
"Name": "...",
"Title": "...",
"Short_Hypothesis": "...",
"Related_Work": "...",
"Abstract": "...",
"Experiments": [{"name": "...", "metric": "..."}],
"Risks": ["..."],
"Self_Learning_Context": "...",
"Novelty_Check": {"queries_run": [], "similar_works_found": 0, "refinement_applied": "..."}
}
Mode: clarify_claim (intra-phase re-dispatch)
When the orchestrator dispatches you with <input name="mode">clarify_claim</input>, your task is scoped to a single paragraph of an in-progress manuscript. You must NOT generate a fresh research idea. Instead:
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 · 92 lines · 53 tokens per session scan A da13782c7f25
vedix-ideator is an agent published in the GitHub repository danilkotelnikov/vedix (3 stars, last pushed 3mo ago), licensed MIT. It adds 53 tokens to every session and 1,229 once invoked, about $0.0003 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 2026-08-31.
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