TeXRA

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Built-in Agent Reference ​

TeXRA ships with built-in agents for common research tasks—polishing prose, fixing errors, creating figures, converting formats, and more. Pick one from the dropdown in the TeXRA UI and you're ready to go.

Agent
polish
Tool-use
chat
research
numerics
review
lean
presenter
latexFixer
latexDiff
setup
creator
Workflow
correct
polish
paper2slide
paper2poster
ocr
transcribe_audio
merge

The agent picker, split by the two agent classes — tool-use (left) and workflow (right) — with the selected agent (polish) highlighted.

Quick Reference ​

Every built-in agent is one of two execution shapes — a tool-use loop or a workflow pipeline:

Tool-use10 agents
researchAnalytical derivations & numerical programming with WolframreviewMathematical and manuscript verificationnumericsDesign, run, and validate computational experimentsleanLean 4 proof developmentpresenterInteractive presentation and poster builderlatexFixerDiagnose and fix LaTeX compile errors, warnings, bad boxeslatexDiffGenerate a visual latexdiff PDF between two versionscreatorDesign, write, and test new TeXRA agentssetupSetup wizard — diagnose, install, configurechatGeneral assistance & file editing (opt-in)
Workflow7 agents
correctFix errors without style changespolishImprove writing qualitypaper2slideConvert papers to beamer slidespaper2posterCreate academic postersocrExtract text from images / PDFstranscribe_audioTranscribe audio to textmergeIntelligently merge document versions

The two shapes behave differently once they run:

Tool-useloop
Instruction
readeditrun tool
repeat
Done

Converse and call tools in a loop until the task is finished.

Workflowpipeline
Input file Edit Diff

Run a fixed input → edit → diff pipeline; hand back a versioned diff.

Tool-use agents loop — converse and call tools until done; workflow agents run a fixed input → edit → diff pipeline and hand back a versioned diff.

Important Note

The underlying prompts and specific behaviors of these built-in agents may change slightly between TeXRA versions as we continue to optimize them. If you require precise, unchanging behavior or wish to heavily customize the process, consider creating a Custom Agent based on these examples.

For details on the underlying structure and execution flow common to all agents, see the Agent Architecture & Execution Flow guide.

Conversational Agents ​

chat ​

Opt-in

chat is no longer included in any of the built-in team presets (Lean Project, Physicist, Mathematician). Enable it from the Agents tab if you want to use it.

A general research companion. It can read your project, edit files, run shell commands, and search through your workspace—all in a back-and-forth conversation.

User story: You just got reviewer comments back. Instead of manually hunting through a 40-page paper, you open chat and paste the reviewer's feedback: "Address comment 3 about missing error bars in Table 2—add them and update the caption." The agent reads your files, makes the edits, and shows you a diff to approve.

Best for: General research assistance, code/LaTeX editing, running compilations

Example instruction:

Review my introduction in paper.tex and suggest improvements for clarity.
Then update the file with your changes.

Research & Discovery Agents ​

research ​

A hands-on research agent that can edit your files and verify mathematics computationally. When you need to check a derivation or run a symbolic calculation alongside your writing, this is the one.

Best for: Mathematical derivations, computational verification, multi-step research

Example instruction:

Derive the variational equations for the Lagrangian in equations.tex.
Verify each step computationally and update the file with results.

numerics ​

A numerical-experiments agent that designs, implements, and validates computational experiments following the scientific method. Use it when a claim needs to be backed by code and reproducible results rather than symbolic derivation alone.

Best for: Convergence studies, benchmarking, simulation-backed results, sanity-checking numerics

Example instruction:

Implement and run a convergence study for the solver in solver.py.
Sweep the step size, plot the error, and report the observed order of accuracy.

Verification Agents ​

review ​

A meticulous scientific auditor that systematically verifies your research manuscript. It checks mathematical correctness, derivation soundness, notation consistency, code-manuscript agreement, and goal achievement — using Wolfram for computational verification.

Best for: Pre-submission audits, mathematical verification, notation consistency checks

Example instruction:

Audit this manuscript: verify every derivation step-by-step, check notation
consistency across all sections, and confirm that every stated goal in the
abstract is actually delivered in the paper.

Formal Methods Agents ​

lean ​

Helps you write and debug Lean 4 proofs. It reads compiler diagnostics, inspects proof state, and iterates until the proof compiles.

Best for: Formalizing proofs, Lean 4 development, Mathlib projects

Example instruction:

Formalize the proof of the theorem in Proofs/GroupTheory.lean. Start with an
informal outline, then produce Lean code and iterate until it compiles.

Presentation & Simplification Agents ​

presenter ​

Builds conference-ready Beamer presentations, posters, and visual materials from your project. Point it at your paper and it reads through your work, plans the slide structure, generates figures, and compiles the result—checking every slide visually before handing it back to you.

Best for: Conference talks, poster sessions, seminar presentations, lightning talks

Example instruction:

Create a 15-slide Beamer presentation from this project. Cover motivation, the core
algorithm, key results, and future work. Use the metropolis theme and include TikZ
diagrams for the architecture.

Correction & Polishing Agents ​

correct ​

The correct agent focuses on fixing errors without changing the style or content of your document (think of it as a meticulous, slightly obsessive proofreader).

Purpose: Fix typos, grammatical errors, and LaTeX syntax issues.

Best for:

  • Final proofreading before submission
  • Fixing errors in collaborative documents
  • Ensuring consistent formatting and notation

Example instruction:

Fix grammatical errors, typos, and LaTeX syntax issues throughout the document.
Ensure consistent notation for mathematical symbols and equations.
Don't change the technical content or writing style.

polish ​

The polish agent improves the writing quality of your document while preserving essential technical content and meaning.

User story: Your draft is technically solid but reads like it was written at 3 AM (because it was). Select polish, tell it "Improve clarity for a CVPR audience—keep all equations and citations intact," and in a couple of minutes you'll have a version that reads like it went through a professional copyedit. Review the colour-coded diff to accept or reject each change.

This agent is ideal for refining drafts that are technically sound but need language improvements before submission.

Example Output ​

Try running polish on the sample document to see a colour-coded diff showing exactly what changed. The agent produces versioned output files with latexdiff highlighting additions in blue and deletions in red.

View example

Content Generation & Transformation Agents ​

paper2slide ​

The paper2slide agent converts research papers into LaTeX beamer presentations.

Purpose: Create presentation slides from academic content.

Best for:

  • Preparing conference presentations
  • Converting papers for teaching purposes
  • Creating seminar materials

Example instruction:

Convert this paper into a beamer presentation with approximately 15-20 slides.
Include a title slide, outline, introduction, methodology, results, and conclusion.
Use bullet points for clarity and add slide titles. Include the key figures and tables.

paper2poster ​

The paper2poster agent transforms papers into academic conference posters.

Purpose: Create well-structured academic posters.

Best for:

  • Conference poster preparation
  • Visual research summaries
  • Academic showcases

Example instruction:

Convert this paper into an academic poster using the baposter template.
Include sections for Introduction, Methodology, Results, and Conclusions.
Highlight key figures and tables. Make it visually appealing with appropriate columns.

Creating figures

There is no longer a dedicated draw agent. To generate or enhance TikZ figures, use a tool-use agent (research or presenter) and describe the figure — the agent writes compilable TikZ, compiles it, and visually verifies the result. See Working with Figures and TikZ Figures.

LaTeX & Build Agents ​

latexFixer ​

Diagnoses and fixes LaTeX compilation errors, warnings, and bad boxes. Point it at a project that won't compile (or compiles with ugly overfull boxes) and it reads the build log, locates the cause, and iterates until the document is clean.

Best for: Resolving build failures, clearing warnings, fixing overfull/underfull boxes

Example instruction:

This project fails to compile. Read the latexmk log, fix the underlying errors,
and rebuild until it produces a clean PDF.

latexDiff ​

Generates a visual diff PDF between two LaTeX versions using latexdiff, so you can see exactly what changed between drafts.

Best for: Reviewing changes between versions, preparing "changes marked" PDFs for co-authors or referees

Example instruction:

Produce a latexdiff PDF comparing the submitted version (v1/main.tex) with the
current revision (main.tex), highlighting additions and deletions.

Figure & Media Agents ​

ocr ​

The ocr agent performs Optical Character Recognition (OCR) on image or PDF files.

Purpose: Extract text content from images or non-searchable PDFs.

Best for:

  • Extracting text from scanned documents or figures
  • Making image-based text searchable and editable
  • Processing figures containing text for analysis

Example instruction:

Perform OCR on the provided image file [figure.png] and extract all text content. Format the output as plain text.

transcribe_audio ​

The transcribe_audio agent converts audio files (like lectures, podcasts, or personal notes) into text transcripts. (Note: Requires native audio support, see Working with Figures).

Purpose: Create searchable text versions of spoken audio content.

Best for:

  • Transcribing recorded lectures or talks
  • Converting podcast episodes to text
  • Transcribing personal voice memos or notes

Example instruction:

Transcribe the provided lecture audio file [lecture.mp3]. Provide the output as plain text, identifying different speakers if possible (e.g., Lecturer, Questioner 1).

Merge Agent ​

merge ​

Takes an AI-edited document and merges the improvements back into your original, keeping the best of both. It understands context, so it won't blindly overwrite your careful phrasing with generic rewrites.

Best for: Applying AI-suggested edits from output files, incorporating reviewer suggestions, combining different drafts

Example instruction:

Merge changes from the edited file into the original document. Prioritize substantive
improvements in clarity while maintaining the original's technical precision.
Preserve mathematical notation and citations from the original.

See Intelligent Merge for details on the merge workflow.

Setup & Meta Agents ​

setup ​

A setup wizard that diagnoses your environment, installs missing dependencies, configures TeXRA, and orchestrates your first task. If you are new to TeXRA or moving to a new machine, start here.

Best for: First-time setup, diagnosing missing dependencies, getting unblocked

Example instruction:

Check whether my environment has everything TeXRA needs, install anything missing,
and help me run my first agent on this project.

creator ​

Designs, writes, and tests new TeXRA agents through conversation. Describe the behavior you want and creator drafts the agent YAML, then helps you refine and validate it.

Best for: Building custom agents without hand-writing YAML from scratch

Example instruction:

Help me build a custom agent that rewrites abstracts to a 150-word limit while
preserving every numerical result. Draft the YAML and walk me through testing it.

Remote Agents ​

The following agents are available as remote agents through the Researcher Access Program. Sign in to TeXRA to access them.

Finds papers and web content for you. Give it a topic and it comes back with relevant preprints, published articles, and web resources. Read-only — it won't touch your files.

Best for: Literature reviews, finding citations, fact-checking

Example instruction:

Find recent papers on transformer architectures for scientific document understanding.
Focus on papers from 2023-2024 that address mathematical equation handling.

discuss ​

A brainstorming partner that can pull in relevant literature as you talk. Useful for thinking through research directions, poking holes in methodology, or connecting ideas across papers. Read-only.

Best for: Brainstorming, methodology critique, research direction guidance

Example instruction:

I'm considering attention mechanisms for my theorem prover. What are the
tradeoffs compared to tree-based approaches? What does the literature say?

simplifier ​

Cuts through complexity in your code and writing. Whether it's duplicated logic across files, overly-abstract wrappers, or LLM-generated filler prose, simplifier cleans things up while preserving correctness.

Best for: Refactoring research code, tightening manuscript prose, cleaning up verbose AI-generated text

Example instruction:

Simplify the numerical solver in solver.py. Look for duplicated code, inline any
single-use helper functions, and remove dead code. Run existing tests after each change.

TIP

Additional remote agents may be available depending on your access level. In the VS Code extension, run TeXRA: View Profile from the Command Palette for the full list. See Remote Agents to sign in and sync them.

Next Steps ​