theta-agent0.3.0
Theta — a science co-researcher agent built as a package for the pi coding agent harness
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Theta (θ)
A science co-researcher agent for the pi coding-agent harness.
Theta is the fundamental parameter of the coalescent — the standard model of how genetic diversity arises — and the universal symbol for the parameters a model fits. One letter, both halves of "computational biology + AI."
Status
Very early development (0.3.0). The architecture, skill-selection plan, and
milestones are being designed in the open. M1 through M3 are built: the theta
launcher plus the Tier-1 research-loop skill library — K-Dense skills vendored
verbatim plus the self-authored theta-research-loop orchestrator (see
Vendored skills) — the first connector skill,
theta-lit-search (PubMed, arXiv, Semantic Scholar; connectors are skills per
ADR 0002), and
the project notebook, theta-notebook (dated provenance entries carrying
content-addressed, graded evidence snapshots, recorded inside the research
loop and after standalone searches per
ADR 0003). The milestones
below continue from there.
What Theta will be
Describe a scientific task in plain language; Theta plans, searches literature, writes and runs code, executes analyses, and reports results with a visible trace — built as a pi package rather than a monolithic fork:
- Skills: curated science skills (literature review, hypothesis generation, experimental design, statistics, domain libraries) following the open Agent Skills specification
- Connectors: literature and database tools (PubMed, arXiv, UniProt, …) as Theta-owned connector skills
- Compute: remote Slurm-cluster jobs via an MCP compute gateway, with a light local sandbox for small tasks
- Models: any of pi's available providers — bring your own key
Theta works today as a pi package from a checkout. The staged plan (M7–M8)
grows it into a standalone theta application with pi embedded as the core
engine — macOS and Linux first, Windows later.
Roadmap
- M1 — package skeleton,
thetalauncher (bin), Tier-1 research-loop skills - M2 — literature connectors (PubMed, arXiv, Semantic Scholar)
- M3 — project notebook: provenance entries with graded evidence
- M4 — compute: Slurm MCP gateway + typed AlphaFold3 tool
- M5 — safety gates + containerized execution
- M6 — eval suite (MCP client is built into pi)
- M7 — standalone
thetashell on pi's headless core (macOS/Linux) - M8 — installers & release channel: Homebrew, deb/AUR, Windows
Install
pi install npm:theta-agent@0.3.0
Requires theta-agent ≥ 0.3.0 on the registry — 0.2.0 and earlier predate the project notebook, and a version-pinned install fails loudly until 0.3.0 is visible. If the registry is not there yet, run Theta from a checkout instead — see Try it.
Try it
theta rides on the pi coding agent, and pi is a peer dependency — install it first. The zero-registry path is a checkout:
git clone https://github.com/hugolld/theta-agent
cd theta-agent
npm i -g @earendil-works/pi-coding-agent
node bin/theta.mjs --dev
node bin/theta.mjs --dev launches pi with this checkout preloaded;
from a checkout you can also name another directory with
$THETA_DEV_ROOT (theta never loads an arbitrary current directory
this way). Theta targets pi ≥ 0.99; if the launcher reports
pi not found, install pi with the command above and retry.
Once theta-agent ≥ 0.3.0 is on the registry (0.2.0 and earlier predate the project notebook — until 0.3.0 is visible, stay on the checkout path above), the installed form is:
npm i -g theta-agent@0.3.0
theta
That launches pi with the Theta package preloaded.
Vendored skills
The research-loop skill library starts from the K-Dense
scientific-agent-skills
library, vendored verbatim per ADR 0001:
upstream names, directory shapes, and content unchanged except a provenance
header in each vendored SKILL.md. Re-syncs happen at milestone boundaries.
Currently vendored (upstream release v2.72.0, commit 526ebce) — the
Tier-1 research-loop set:
literature-review— systematic, scoping, and narrative literature reviews with reproducible searches and citation checkspaper-lookup— searches 18 scholarly APIs for papers, citations, abstracts, and open-access full text with reproducible provenancepaperzilla— reads Paperzilla projects, searches project feeds, and retrieves recommendations and canonical papersbgpt-paper-search— searches BGPT scientific papers by topic or DOI and retrieves claim-level evidence from full textresearch-lookup— compiles current scholarly evidence for manuscripts and research briefs via Parallel Search, Extract, and Researchcitation-management— citation search, metadata validation, and BibTeX generation across OpenAlex, PubMed, and Google Scholarpyzotero— manages Zotero reference libraries through the pyzotero Python client and the Zotero Web APIpeer-review— evidence-bounded, constructive peer-review drafts and structured manuscript assessmentsscholar-evaluation— qualitative-first, evidence-traceable developmental review of scholarly works and research-assessment rubricsscientific-writing— drafts, revises, and audits manuscripts with explicit evidence provenance and reporting-guideline coveragescientific-critical-thinking— evaluates scientific claims and evidence quality: validity, bias, confounders, and evidence gradingscientific-brainstorming— evidence-aware scientific ideation with structured discussion, adversarial review, and decision logshypothesis-generation— evidence-bounded candidate hypotheses, rival explanations, and preregistration-ready analysis planshypogenic— plans and audits LLM-assisted hypothesis generation from labeled text datasets with HypoGeniC/HypoRefineexperimental-design— designs experiments before data collection: randomization, blocking, factorial designs, and treatment layoutsstatistical-analysis— guided test selection, assumption checking, effect sizes, power analysis, and APA-formatted reportingstatistical-power— sample-size and power calculation, closed-form and simulation-based, for study planninguncertainty-and-units— unit tracking and measurement-uncertainty propagation in scientific calculationsexploratory-data-analysis— bounded, local first-pass analysis profiles of supported scientific file formats
The theta-research-loop orchestrator that routes the research loop into the
library is Theta's own, self-authored work.
One deliberate omission: pi-agent, a Tier-1 candidate that documents the pi
harness itself. It would duplicate pi's own documentation, drift against
installed pi releases, and add nothing to the research loop. The skip is
recorded on issue #5.
K-Dense's skills are MIT-licensed, © K-Dense Inc. If you use them in research, please cite their paper:
Kassis, T., Agarwal, V., He, Y., Patel, D., & Brueckner, A. M. (2026). Scientific Agent Skills: A Library of Procedural Knowledge for Research Agents. arXiv:2609.00065. https://doi.org/10.48550/arXiv.2609.00065
License
MIT