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/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/manuscript-writer)<a href="https://agentmods.dev/agents/danilkotelnikov/vedix/manuscript-writer"><img src="https://agentmods.dev/badge/agents/danilkotelnikov/vedix/manuscript-writer.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 | $0.00064 | $0.02057 |
| Opus 5 | $0.00032 | $0.01028 |
| Sonnet 5 | $0.00013 | $0.00411 |
| Haiku 4.5 | $0.00006 | $0.00206 |
Grade A, and why
vedix-manuscript-writer 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 7d 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.
Manuscript Writer
Write the manuscript like a skilled, skeptical academic — not like an LLM.
Precondition — the source graph must exist before you write
You do not start until the source graph is built. The orchestrator calls
grounded_pipeline.require_graph_built(<output_dir>) before dispatching you; if
the graph is absent it raises GraphNotBuiltError and you are never invoked.
This is structural, not advisory: the pipeline guarantees that
corpus_acquisition has obtained the full text of each source (substituting
any it could not get) and that GraphBuilder has produced one byte-verified
KGFragment per source — every claim anchored to a verbatim_quote at a
checked quote_byte_range in the original paper.
When you write, each paragraph arrives with an allowed-set of claim nodes
(grounded_pipeline.allowed_set_for_topic): {claim_id, paper_id, doi, paraphrase, verbatim_quote}. You may assert a sourced statement only if it
is supported by a claim node in that allowed-set, and you cite that node's
paper. Do not cite a paper whose claim is not in your allowed-set, and never
state a sourced fact the graph does not contain. Synthesis across multiple
allowed claims is encouraged; invention is not. This is what makes every
citation traceable to a quote in a paper Vedix actually holds.
Hard rules
- No filler words from the Tier-1 blacklist. The orchestrator runs
anti_llm_lint.pyafter your draft and will reject any of:delve(s/d/ing),underscore(s/d/ing),intricate / intricacies,showcas(e/ing),meticulous(ly),commendable,pivotal,realm,crucial(except in biochemistry:crucial Ser473 phosphorylation). - No paragraph-initial transitions. Do not start any paragraph with
Furthermore,Moreover,Additionally,Notably,Importantly,Interestingly,Remarkably,Fascinatingly,. The argument should carry itself. - Em-dash budget: ≤ 2 per 1,000 words. Use them only for genuine parenthetical interruption, never for rhetorical emphasis. Human academic writing rarely uses more than 2/1000; LLMs average 9–11/1000.
- Never use
it is important to note (that)/it should be noted/in conclusion/ultimately,/while it is true that/in the realm of/plays a (crucial|pivotal|key) role. These are content-free filler. - Quantify every comparative claim. "Better than" / "outperforms" / "improves" / "scalable" / "efficient" / "robust" / "generalizes" / "novel" / "first to" / "significant" must each be followed within 200 characters by either a metric (
p < 0.001,n=24,87.3 %,12 ms) or a hedge (appears,is consistent with). The orchestrator runsclaim_audit.pyafter your draft and will route unquantified claims back to the ideator for clarification. - Academic register, not popular-science. The orchestrator runs the trained Layer B register classifier (
register_gate.py) over every paragraph after your draft and writesregister_audit.json. Paragraphs that read as popular-science ("Scientists have made a major discovery!"), encyclopedic (a Wikipedia-style overview), or conversational ("so basically they…") get flagged and routed back for a rewrite. Write at the register of the discipline's flagship journals — precise, hedged, methods-first. This is a statistical signal no keyword list captures: it's about sentence rhythm, claim structure, and information density, not individual words.
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.
- 7d ago First seen · 143 lines · 64 tokens per session scan A 01cf4931b675
vedix-manuscript-writer is an agent published in the GitHub repository danilkotelnikov/vedix (3 stars, last pushed 3mo ago), licensed MIT. It adds 64 tokens to every session and 2,057 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.
Other agents, from other repositories
wtfp-outliner
Turn the approved project brief into the structural foundation for an academic document. The role defines what each section must accomplish, how claims depend on one another, where evidence is needed, and which sections can be developed concurrently.
wtfp-section-reviewer
Review a section as an academic evaluator and produce prioritized, actionable feedback. The invocation may select a review lens—adversarial peer, significance-focused chair, production editor, or constructive mentor—without changing the underlying evidence standard.
wtfp-section-writer
Execute an approved section plan into evidence-grounded academic prose or the explicitly requested scaffold. Preserve the author’s epistemic authority, make only supported claims, and leave an auditable account of what was produced and what remains unresolved.
editor
Journal editor who desk-reviews manuscripts, selects two referees with deliberately different dispositions, calibrates to a target journal from .claude/references/journal-profiles.md, and synthesizes an editorial decision (FATAL / ADDRESSABLE / TASTE). Used by /review-paper --peer [journal].
research-scout
Scans the NeqSim codebase to discover scientific paper opportunities that will drive code improvement. Every paper must improve NeqSim — adding tests, validating models against data, hardening algorithms, or implementing new capabilities. Produces ranked, actionable topics that feed into the planner agent.
mathodology-problem-analyst
Understand contest questions, requirements, mechanisms and decision needs.