ara-labs

@ara-labs source repo

8 skills
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6 hours ago last updated

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Compiler · ara-labs bundle
Universal ARA Compiler. Converts ANY research input — PDF papers, GitHub repositories, experiment logs, code directories, raw notes, or combinations thereof — into a complete Agent-Native Research Artifact (ARA): a structured, machine-executable knowledge package with a cognitive layer (claims, concepts, methods), an artifact layer (code/configs/data as the work warrants), an exploration graph (research DAG), and grounded evidence. Works across any research field — not only model-training research. TRIGGERS: compile, create ARA, generate artifact, convert paper, build artifact, compile paper, ARA from PDF, ARA from repo, ARA from code, structure research, extract knowledge, extract figure data, digitize plot, read chart, figure to data

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Submit Ara · ara-labs bundle
ARA Submitter. Takes a research directory, makes sure it is a valid Agent-Native Research Artifact (ARA) — compiling it with the `compiler` skill when it is not — guarantees it carries an interactive visualization (`research-visualizer`), then publishes it to the ARA Hub and hands back one link plus an update token. The token is stored in the artifact's own `.ara_env`, so the next submission of the same work REPLACES it in place instead of creating a second entry. Publishes through the user's GitHub account when they have one, and straight to the Hub when they do not — no account required either way. TRIGGERS: submit, submit ara, publish ara, upload ara, share ara, push ara to github, add to ara hub, submit-ara, publish artifact, make my ara public, submit to a conference, update my submission, resubmit

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Context Drop · ara-labs bundle
Context Drop. Hands a file, a folder, or a set of notes to somebody else's agent as one URL. Uploads the path to the ARA Hub, then prints a share link plus a ready-to-paste prompt: the recipient's agent fetches the drop as a single Markdown document holding every text file, with binaries listed as URLs to pull on demand. Also the reader — given a drop link, it pulls the bundle and works from it. Replaces pushing a throwaway repo to GitHub or mailing a zip nobody's agent can open. TRIGGERS: context drop, drop, share this folder, share these files, send this directory, give this to my friend's agent, share context, make a link for this folder, upload this folder, share notes with an agent, read this drop, open a drop link, agenticresearch.sh/drop

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Rigor Reviewer · ara-labs bundle
ARA Seal Level 2: Semantic Epistemic Review. Acts as an objective research reviewer for Agent-Native Research Artifacts. Assumes Level 1 structural validation has already passed. Evaluates six dimensions of epistemic quality through semantic reasoning over the ARA's content. Produces a scored review with per-dimension strengths/weaknesses/suggestions, severity-ranked findings, and an overall epistemic-quality tier (Exemplary to Unsound). TRIGGERS: level2, seal level 2, verify level 2, epistemic audit, review ara, audit claims

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Research Fuzzer · ara-labs bundle
Treat an open-ended investigation the way a fuzzer treats a program. After every action, reflect on two things a fuzzer always knows and an agent never does: did anything NEW happen, and where have I NOT been yet. Keeps an append-only notebook of predictions and outcomes; reports what you explored, the leads you saw but never followed, unexplained results, and a going-in-circles alarm. Use for ANY investigation without a known map: research experiments, debugging, data analysis, literature or market research, evaluations. Fire it (1) when starting an investigation, (2) after every action or batch of actions that returned results, (3) before stating any conclusion. Skip it for trivial single-step tasks.

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Research Manager · ara-labs bundle
End-of-turn research process recorder with progressive crystallization. Invoked at the END of EVERY turn, after the user's current request has been fully addressed and before yielding control back to the user. Reviews what happened in the turn, extracts research-significant events, and writes them into the ara/ artifact through a three-stage pipeline: Context Harvester → Event Router → Maturity Tracker. Trace events (decisions, experiments, dead ends, pivots) are recorded immediately as journey facts. Knowledge events (claims, heuristics, concepts, constraints) are staged first and crystallize into typed layers ONLY when closure signals appear — topic abandonment, verbal affirmation, empirical resolution, or artifact commitment. NEVER mid-turn. All entries carry provenance tags (user / ai-suggested / ai-executed / user-revised). Also supports optional, user-triggered taste comments — free-form evaluative reactions to a claim, heuristic, or trace node — independent of the crystallization pipeline.

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Research Foresight · ara-labs bundle
ARA World Model — read-only reasoning engine over ONE Agent-Native Research Artifact (ARA), run LOCALLY with the coding agent itself as the LLM (no SDK, no API key). Given an ARA directory and a free-text query, it answers any question about the ARA — a forward "what if I change X", but equally why-did-this-work, what-should-I-try, is-this-sound, how-do-these-compare, or anything else — by retrieving precedent from the ARA's native files (references/RETRIEVE.md) and answering as the Predictor (references/PREDICT.md): a bold, grounded, falsifiable Answer shaped to what the question actually calls for. TRIGGERS: ask the world model, wm predict, predict with the world model, what if I change X, forecast the loss curve, will this help, why did this work, what should I try next, is this claim sound, compare these, retrieve precedent, what precedent surfaces.

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Research Visualizer · ara-labs bundle
Research Visualizer. Renders an existing Agent-Native Research Artifact (ARA) into ONE self-contained, interactive HTML file showing the AI scientist's step-by-step research process: a clickable process map of the exploration tree (branches and dead ends included) on the left, and a per-step drill-down on the right — what the step did (its narrative written in plain language a person can follow), why (the linked claim), the real result (verbatim grounded numbers + inline figures + tables), and the code/artifact pointer. Read-only consumer of the artifact — it never changes how research is done. When the ARA carries them, it also surfaces (each optional, only when present) the related-work dependency graph, the problem framing, a concepts glossary with in-text term popovers, and the solution recipes — reached from header disclosures without leaving the process map. Accepts either an existing ARA or raw research input (a paper, repo, run logs, or notes); when the input is not yet an ARA it is compiled into one

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8 published skills