FBA simulation agent. Runs standard FBA, parsimonious FBA, Flux Variability Analysis, and gene/reaction knockout simulations using COBRApy. Use after a validated metabolic model is available and the user wants to compute growth rates, flux distributions, or knockout phenotypes.
Metabolic flux analysis agent. Performs gene essentiality analysis, phenotypic phase plane construction, flux sampling, and subsystem-level pathway analysis. Use after FBA simulations are complete and the user wants deeper phenotypic characterisation or to identify metabolic engineering targets.
Metabolic phenotype interpretation and publication figure agent. Compares wild-type vs. mutant flux distributions, predicts maximum theoretical product yields, identifies metabolic bottlenecks, and generates publication-quality metabolic maps and charts. Use after flux analysis is complete and the user needs…
Grounded secretary for Anti-Slop Brain. Use for source-cited questions about detection and repair of AI slop in prose, code, documentation, and agent output, grounded in corpus evidence rather than authorship detection, vault maintenance, claim review, release hygiene, and read-only advisory workflows. Reads the brain…
Read-only slop grader for prose, documentation and agent output. Returns findings with severity and confidence on separate axes, a verbatim quote for every finding, and the artifact from the structural test that produced it. Never rewrites, never edits, never states or implies who or what wrote the text. Use for a…
Fresh-context adversarial verifier. Given an artifact and an existing slop review or rewrite, it independently re-checks the claims, the citations, the package names, the scanner results, and the review's own discipline. It tries to break the review rather than confirm it. Reports which findings survive, which are…
An experiment-planning specialist for a research workflow. It turns a confirmed technical approach into a structured plan of experiments or computing tasks, including timing, methods, variables, and success measures.
Sub-agent that parses bibliographic sections and inline citations from SOTA / article text. Takes raw text (a section header + content, or an inline excerpt) and returns structured JSON [{author, year, title, doi?, venue?, raw}]. Isolates the LLM extraction from the main agent context. Invoke from the INGEST pipeline…
Sub-agent that audits a specific claim against the PDF cited. Invoked by citation-receipts skill for deep PDF↔claim verification. Returns structured verdict (VALID/ADJUST/INVALID/UNVERIFIABLE) with evidence quoted from the source. Isolates the heavy PDF reading from the main agent's context.
Sub-agent that performs exhaustive multi-source academic search (paper-search MCP across 22 platforms + optional NotebookLM + optional WebSearch). Returns structured JSON of candidate refs for sota-writer phase A. Invoke when broad literature search is needed without polluting the main agent's context.