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/hevangel/dvcon_ai_library/dvcongit clone --depth 1 https://github.com/hevangel/dvcon_ai_libraryWrote 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/hevangel/dvcon_ai_library/dvcon)<a href="https://agentmods.dev/commands/hevangel/dvcon_ai_library/dvcon"><img src="https://agentmods.dev/badge/commands/hevangel/dvcon_ai_library/dvcon.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 | $0.00026 | $0.00359 |
| Opus 5 | $0.00013 | $0.00179 |
| Sonnet 5 | $0.00005 | $0.00072 |
| Haiku 4.5 | $0.00003 | $0.00036 |
Grade A, and why
dvcon 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 5d 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.
What it actually says
Use the dvcon MCP server tools to handle this request against the DVCon paper corpus:
$ARGUMENTS
Follow this flow:
- If the request looks like a search or topic question, call
dvcon__search_paperswith the query (hybrid mode by default). Present the top results as a numbered list withpaper_id, title, year, location, and a one-line snippet. - If the request names or implies a specific paper, call
dvcon__get_paper_detailanddvcon__get_paper_markdownfor thatpaper_idand answer from the extracted content. - If the request asks for synthesis, comparison, or summarization across one or more papers, call
dvcon__chat_with_paperswith the resolvedselected_paper_idsand the user's question. Cite claims with the returned[n]citation labels. - If the request asks for corpus size or coverage, call
dvcon__corpus_stats.
Rules:
- Always cite the
paper_id(and title + year when space allows) when referencing a paper. - If a tool returns an
errorfield, surface that error verbatim instead of fabricating content. - Never invent DVCon paper content that did not come back from a tool call.
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.
- 5d ago First seen · 22 lines · 26 tokens per session scan A 7fb2ce402027
dvcon is a command published in the GitHub repository hevangel/dvcon_ai_library (11 stars, last pushed 7d ago), licensed MIT. It adds 26 tokens to every session and 359 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
verify-math
Verify a self-authored mathematical result end to end by routing claims across adversarial review, numerical falsification, symbolic or CAS checks, and Lean, then aggregating one report. Use when a theorem, proposition, conjecture, or paper-wide mathematical argument needs the appropriate combination of verification…
master_analysis
Run comprehensive 5-phase analysis across labs, genetics, and protocols.
replication-package
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diff
Quantitative volume comparison between a CadQuery model and a reference STEP file.
arg-diagram
ARG academic-paper diagram mode — standalone structural & conceptual diagram generation.
simulation-calibrator
Test and refine simulation accuracy with validation loops, bias detection, and continuous improvement frameworks.