Scientific Runtime Protocol
This is a shared runtime skill for scientific CLI work.
It is not a tool manual. It tells the agent how to behave when serving real users on scientific tool tasks.
Use it alongside a tool-specific scientific skill such as:
quantum-espressolammpsgromacsopenfoambioinformatics
Core Principle
ScholarAIO is for users, not for people who want to co-maintain the internal documentation layer.
So the agent should absorb complexity whenever possible.
The user should experience:
- natural language help
- reliable parameter lookup
- graceful fallback when coverage is partial
The user should not experience:
- being asked to manually patch
toolref - being forced to learn internal parser gaps
- being blocked because a documentation layer is imperfect
Runtime Protocol
For any scientific CLI task:
- Identify the scientific tool or sub-tool that matches the problem.
- Use the tool-specific skill for workflow and scientific norms.
- Use
toolreffirst for commands, parameters, program pages, and option meanings. - If
toolrefis sufficient, continue normally. - If
toolrefis partial, fall back to official docs and continue the task. - Mention the coverage gap briefly only when it affects confidence or maintainability.
- Do not turn the current user task into documentation maintenance work.
Toolref-First Behavior
The agent should prefer:
scholaraio toolref show <tool> ...for precise lookupsscholaraio toolref search <tool> "..."for natural-language entry
The stable public surfaces are:
- the
scholaraio toolref ...CLI - the top-level
scholaraio.stores.toolrefpackage facade
The agent should not route users through internal implementation modules such as:
scholaraio.stores.toolref.fetchscholaraio.stores.toolref.manifestscholaraio.stores.toolref.storagescholaraio.stores.toolref.search
Those internal module boundaries may change during refactors. User-facing guidance should stay anchored to the CLI and the top-level package behavior.
Before writing configuration or scripts, first resolve:
- which program or subcommand is relevant
- which parameters are high-risk
- which defaults or restrictions matter for validity
When Toolref Is Incomplete
If toolref does not fully answer the question:
- continue using the official documentation source
- clearly separate "task progress" from "maintenance opportunity"
- do not ask the user to stop and repair the docs layer first
- do not expose internal refactor details unless they materially affect current behavior
Use this pattern:
- "I used
toolreffor the main entry point." - "For this deeper detail, I fell back to the official docs because current coverage is partial."
Escalation Rule
Escalate a gap to onboarding or maintenance only when:
- the same gap appears repeatedly
- it blocks a common task
- it affects correctness, not just convenience
If it is a one-off edge case, do not derail the user task.
Separation Of Responsibilities
- tool-specific skill: when to use the tool, workflow, scientific norms
toolref: interface and parameter reference- scientific runtime: how to behave under uncertainty or partial coverage
When code changes are involved:
- preserve the public
scholaraio.stores.toolrefentry surface - treat package-internal reorganizations as an implementation detail
- if a refactor changes behavior visible through CLI or top-level imports, treat that as a regression until proven otherwise
Anti-Patterns
Do not:
- dump raw flags from memory
- tell the user to "go improve toolref first"
- confuse a successful CLI run with a valid scientific result
- replace scientific judgment with parameter lookup alone
- instruct the user to use internal module names as if they were the supported interface
Output Style
When answering the user:
- keep maintenance details short
- foreground scientific progress and decision-making
- mention fallback only when it materially changes confidence or provenance