deerwork-ai
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deer-workflow
An open-source Dynamic Workflow runtime that combines deterministic TypeScript orchestration with replaceable Agent runtimes.
AI repository intelligence
FR-AI / ANALYSISWhy it is worth attention
It emphasizes data provenance and immutability by preserving every snapshot, enforces publication integrity through byte-matching checks, and provides a secure two-checkout sync mechanism—all with zero third-party Python dependencies.
Who it is for
- Researchers seeking funding or compute resources for AI-for-science projects
- Grant administrators managing scientific computing allocations
- Open science advocates who need transparent and verifiable resource tracking
- Developers building tools that rely on curated, versioned opportunity data
Use cases
- Discovering currently open scientific computing grants and API credits
- Auditing historical funding opportunities through immutable snapshots
- Syncing the same dataset across a primary site and a mirror with integrity guarantees
- Validating data integrity and provenance before publishing new snapshots
Strengths
- Immutability: every record state is preserved with lifecycle fields and full history snapshots
- Zero external dependencies: build and validation run on standard library Python 3.10+
- Rigorous testing: comprehensive test suite validates schema, boundaries, lifecycle invariants, and synchronization
- Secure sync: the sync helper ensures byte-identical distribution across checkouts without deletion or unwanted edits
Considerations
- Snapshot dated 2026-07-29 may not reflect current availability of opportunities
- Publication requires manual owner action and reviewed local commands—no automated deployment
- Limited dataset: only 48 public records in the initial snapshot
README quick start
Scientific Resources
A static, official-source tracker for scientific compute allocations, cloud and API credits, and AI-for-science or open-science grants.
- Primary:
- Synchronized mirror:
- Source repository:
Earth-Space-AI/scientific-resources
The inspected primary route normalizes its canonical and social URL to the slashless https://earth-space-ai.org/scientific-resources. The mirror intentionally remains self-canonical at https://huangzesen.github.io/scientific-resources/ and links to the primary as its alternate.
Snapshot scope
The canonical public dataset is a reviewed snapshot dated 2026-07-29 (America/Los_Angeles), with collection verification timestamp 2026-07-30T01:16:56Z. The configured Pacific date did not roll over. The dataset contains 48 public records: 32 actionable open, 1 actionable upcoming, and 15 archived. These are preserved snapshot facts, not a claim that the same statuses remain current today.
A specific modeled cycle with an officially verified fixed applicant deadline on or before page_date + 15 calendar days is moved out of the actionable view. The boundary is inclusive and group-neutral. Policy archival is not a claim that the sponsor closed intake: the record preserves its official deadline and sources, removes its apply control, and shows a public retirement_reason. A continuously open program with recurring cutoffs advances to the next verified cutoff outside the fence rather than closing the whole program; a multi-element umbrella has no single fixed deadline.
data/opportunities.json is the sole canonical current opportunity data file. Every stable ID remains present after publication; retirement is represented with lifecycle fields, not by deleting the record. Each current record carries first_seen, last_verified, retired_at, retirement_reason, superseded_by, and reactivated_at. The exact original 32-record dataset is preserved as the first immutable history snapshot at data/history/snapshots/2026-07-28-a5af1ed92d34/.
Build
Requirements: Python 3.10 or newer; no third-party Python packages.
python3 src/generate.py
The production build writes the current data, provenance, and immutable history files to each host profile:
dist/primary/index.html
dist/primary/public_opportunities.json
dist/primary/provenance.json
dist/primary/snapshots/in
Description
Public, reproducible tracker for scientific compute, cloud/API credit, and research funding opportunities.
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