scholaraio
AGENTS.md585 starsChanged 3 months agoMITView on GitHub
This is the repository entry document for coding agents. It is intentionally short: ScholarAIO is an All-in-One academic harness for agents. Researchers work through a coding agent to search literature, inspect evidence, organize persistent project context, produce reviewable research outputs, and use bounded scientific-tool adapters without ScholarAIO replacing the agent's native reasoning or orchestration. The Python package is scholaraio. Real work should usually happen through the ScholarAIO CLI and project skills, not by bypassing runtime helpers with ad hoc file…
Where files are headingNew AGENTS.md files have more rules about keeping secrets out of the code, and fewer about code style.
Of the AGENTS.md files we read, the 31,542 first seen in the last six months, against the older ones: the kind of rule that gained most share, and the kind that lost most. About files like this in general, not this one, and an estimate, since a kind is a pattern in the words.
In this repository47 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- .github/copilot-instructions.mdCopilot instructions
- .cursor/rules/scholaraio.mdcCursor rule
- academic-writingSkill
- arxivSkill
- auditSkill
- backupSkill
- bioinformaticsSkill
- citation-checkSkill
- citationsSkill
- documentSkill
- drawSkill
- enrichSkill
- exploreSkill
- exportSkill
- graphSkill
- gromacsSkill
- importSkill
- indexSkill
- ingestSkill
- insightsSkill
- lammpsSkill
- literature-reviewSkill
- metricsSkill
- nature-workflowSkill
- openfoamSkill
- paper-guided-readingSkill
- paper-writingSkill
- patent-fetchSkill
- patent-searchSkill
- posterSkill
- publishSkill
- quantum-espressoSkill
- renameSkill
- research-gapSkill
- review-responseSkill
- scientific-runtimeSkill
- scientific-tool-onboardingSkill
- scrubSkill
- searchSkill
- setupSkill
- showSkill
- technical-reportSkill
- topicsSkill
- translateSkill
- workspaceSkill
- writing-polishSkill
The file
Show its rules and text
We split this AGENTS.md into the rules it gives an agent
13 rules. About 0 are common, 9 are distinctive, and 4 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈9
Distinctive · estimate
This author's own choices. Worth a look.
4
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 5
keep durable project facts and hard constraints here
- Very specific: line 17
Prefer a matching project skill in .claude/skills/ when the user request clearly maps to one.
- Very specific: line 18
Use the scholaraio CLI to do real work instead of only describing what should be done.
- Distinctive: line 20
Treat paper conclusions as claims, not facts.
- Very specific: line 21
Keep user-facing drafts, reports, exports, and research outputs under workspace/, not the repository root or scholaraio/.
- Very specific: line 22
Do not casually rewrite or delete runtime data.
- Distinctive: line 23
When changing runtime layout, compatibility behavior, agent entry docs, or skill discovery, update tests and aligned docs in the same …
- Distinctive: line 24
After code or doc changes, run the relevant checks and at least one real smoke path when feasible.
- Distinctive: line 28
Read these in roughly this order:
- Distinctive: line 52
If a workflow has grown into a reusable playbook, move it into a skill instead of expanding this file.
- Distinctive: line 121
Keep these wrappers lightweight.
- Distinctive: line 125
Use the smallest doc that answers the question:
- Distinctive: line 136
When in doubt, keep this file short, keep skills procedural, and keep deep detail in dedicated reference docs.
≈ “Common” is an estimate: at least 1 in 5 of the 40,246 AGENTS.md files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
ScholarAIO - Agent Entry
This is the repository entry document for coding agents. It is intentionally short:
- keep durable project facts and hard constraints here
- move multi-step procedures into skills
- move deep reference material into the indexed
docs/knowledge base
What ScholarAIO Is
ScholarAIO is an All-in-One academic harness for agents. Researchers work through a coding agent to search literature, inspect evidence, organize persistent project context, produce reviewable research outputs, and use bounded scientific-tool adapters without ScholarAIO replacing the agent's native reasoning or orchestration.
The Python package is scholaraio. Real work should usually happen through the ScholarAIO CLI and project skills, not by bypassing runtime helpers with ad hoc file edits.
How To Work In This Repo
- Prefer a matching project skill in
.claude/skills/when the user request clearly maps to one. - Use the
scholaraioCLI to do real work instead of only describing what should be done. - Load information progressively. Prefer metadata or abstracts first, then conclusions or full text only when needed.
- Treat paper conclusions as claims, not facts. Compare evidence, point out limitations, and distinguish supported results from author interpretation.
- Keep user-facing drafts, reports, exports, and research outputs under
workspace/, not the repository root orscholaraio/. - Do not casually rewrite or delete runtime data. When touching runtime layout, use
Config, migration helpers, and tested accessors. - When changing runtime layout, compatibility behavior, agent entry docs, or skill discovery, update tests and aligned docs in the same change.
- After code or doc changes, run the relevant checks and at least one real smoke path when feasible.
Start Here
Read these in roughly this order:
README.mdfor the product overview and top-level structure.STRATEGY.mdbefore changing product scope or adding an external integration.docs/DESIGN.mdfor the repository knowledge map.docs/getting-started/agent-setup.mdfor repo-open vs plugin or cross-project setup.docs/guide/cli-reference.mdfor the current user-facing CLI surface.docs/guide/agent-reference.mdfor deeper agent, runtime, and skill organization details.docs/internal/PLANS.mdanddocs/internal/exec-plans/completed/scholaraio-upgrade-plan.mdbefore changing runtime layout, migration, or compatibility behavior.
Skill-First Workflow
The canonical project skill source is .claude/skills/. Cross-agent discovery paths are wrappers around that same source:
.agents/skills/.qwen/skills/skills/
Representative skills to check first:
- Core research:
search,show,ingest,workspace,audit,translate - Writing:
academic-writing,nature-workflow,literature-review,paper-guided-reading,paper-writing,citation-check,writing-polish,review-response,research-gap,poster,technical-report - Outputs and tooling:
draw,document,publish,scientific-runtime,scientific-tool-onboarding
If a workflow has grown into a reusable playbook, move it into a skill instead of expanding this file.
Repo Map
scholaraio/core/: config, logging, and shared runtime foundationsscholaraio/providers/: external service clients and parsing backendsscholaraio/stores/: persistent library roots and storage helpersscholaraio/projects/: user project and workspace behaviorscholaraio/services/: domain logic and orchestrationscholaraio/interfaces/cli/: CLI parser, startup, and command handlers
The breaking cleanup generation removed legacy root-level public facades such as
scholaraio.index, scholaraio.workspace, and scholaraio.translate. New code
should import canonical namespaces directly.
High-signal canonical implementation pointers:
scholaraio/stores/explore.pyscholaraio/projects/workspace.pyscholaraio/services/insights.pyscholaraio/services/translate.pyscholaraio/interfaces/cli/scholaraio/interfaces/cli/compat.pyfor internal CLI wiringscholaraio/cli.pyas the published entrypoint only
Current Runtime Model
- Runtime is fresh-layout-only under
data/libraries/,data/spool/, anddata/state/. - Legacy roots such as
data/papers/,data/explore/,data/proceedings/, anddata/inbox*are no longer normal runtime inputs. Usescholaraio migrate upgrade --migration-id <migration-id> --confirmfor the one-command supported migration, orscholaraio migrate ...to inventory, verify, and run individual stores. workspace/<name>/stays a free-form user project tree.- Workspace paper references live in
workspace/<name>/refs/papers.json. workspace.yamlis additive metadata only; it does not replacerefs/papers.json.- System-owned workspace outputs live under
workspace/_system/, especially:workspace/_system/translation-bundles/workspace/_system/figures/workspace/_system/output/
- Runtime-layout migration control lives under
.scholaraio-control/. The standardized one-command upgrade gate isscholaraio migrate upgrade --migration-id <migration-id> --confirm;finalizeremains the post-store cleanup/final verification step.
Commands To Know
scholaraio --help- For repo-local validation, prefer
python -m scholaraio.cli ...so you are exercising the current checkout instead of an older installed console script. scholaraio setup checkscholaraio search --helpscholaraio show --helpscholaraio gui --helpscholaraio pipeline --helpscholaraio ws --helpscholaraio migrate --helpscholaraio migrate upgrade --helpscholaraio migrate finalize --help
Common verification commands in this repo:
python -m pytest -q -p no:cacheproviderpython -m ruff check scholaraio testspython -m ruff format --check scholaraio testspython -m mkdocs build --strict
Multi-Agent Entry Points
- Claude Code:
CLAUDE.md+.claude/skills/ - Codex / OpenClaw:
AGENTS.md+.agents/skills/ - Qwen:
.qwen/QWEN.md+.qwen/skills/ - Cursor:
.cursor/rules/scholaraio.mdc, thenAGENTS.md - Cline:
.clinerules, thenAGENTS.md - Windsurf:
.windsurfrules, thenAGENTS.md - GitHub Copilot:
.github/copilot-instructions.md, thenAGENTS.md
Keep these wrappers lightweight. Do not turn every wrapper into a second full manual.
Deep Reference
Use the smallest doc that answers the question:
- Repository knowledge map:
docs/DESIGN.md - Plan map and execution history:
docs/internal/PLANS.md,docs/internal/exec-plans/ - Knowledge quality and cleanup:
docs/internal/QUALITY_SCORE.md - Agent and skill organization:
docs/guide/agent-reference.md - Setup and installation:
docs/getting-started/agent-setup.md,docs/getting-started/installation.md,docs/getting-started/configuration.md - CLI behavior:
docs/guide/cli-reference.md - Writing workflows:
docs/guide/writing.md - Runtime layout and migration:
docs/internal/exec-plans/completed/scholaraio-upgrade-plan.md,docs/design-docs/directory-structure-spec.md,docs/design-docs/directory-migration-sequence.md,docs/design-docs/migration-mechanism-spec.md
When in doubt, keep this file short, keep skills procedural, and keep deep detail in dedicated reference docs.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

