aio-prototype
Skill0 starsChanged 30 days agoMITView on GitHub
Run a bounded backend architecture spike to resolve a specific technical uncertainty.
In this repository54 other files it gives its agents.
- agent-workflowsSkill
- aio-agentsSkill
- aio-algorithmsSkill
- aio-apiSkill
- aio-architectureSkill
- aio-autoplanSkill
- aio-benchmarkSkill
- aio-brainstormSkill
- aio-canarySkill
- aio-checkpointSkill
- aio-ciSkill
- aio-commitSkill
- aio-compoundSkill
- aio-dataSkill
- aio-debugSkill
- aio-devex-reviewSkill
- aio-doc-reviewSkill
- aio-explainSkill
- aio-feedbackSkill
- aio-handoffSkill
- aio-ideateSkill
- aio-observeSkill
- aio-optimizeSkill
- aio-pipelinesSkill
- aio-plan-reviewSkill
- aio-planSkill
- aio-proofSkill
- aio-qa-onlySkill
- aio-qaSkill
- aio-releaseSkill
- aio-resumeSkill
- aio-reviewSkill
- aio-securitySkill
- aio-shipSkill
- aio-simplifySkill
- aio-specSkill
- aio-tddSkill
- aio-test-auditSkill
- aio-testSkill
- aio-verifySkill
- aio-workSkill
- aio-worktreeSkill
- all-in-oneSkill
- apple-appstore-reviewerSkill
- backend-algorithmsSkill
- backend-debugSkill
- backend-pipelinesSkill
- backend-planSkill
- backend-reviewSkill
- backend-verifySkill
- complete-destructionSkill
- launch-readinessSkill
- play-policy-insightsSkill
- reverse-engineer-anythingSkill
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 8
Run a bounded backend architecture spike to resolve a specific technical uncertainty.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill 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
AIO Prototype
Run a bounded backend architecture spike to resolve a specific technical uncertainty.
Protocol
- State the falsifiable question, competing mechanisms, workload, success threshold and effort/time ceiling. Do not run a spike when existing repository evidence already answers it.
- Build the smallest isolated experiment needed for the decision, keeping secrets and production data out. Test the actual boundary: replay, query plan, cancellation, concurrency or model/tool budget, rather than a decorative demo.
- Record commands, versions, raw results and failure cases. Keep stubbed services and synthetic data clearly identified; a passing simulation cannot establish production readiness.
- Compare alternatives and update the decision record. Preserve useful evidence and explicitly decide whether prototype code is discarded, hardened or reused after proper acceptance tests.
Return and handoff
A bounded experiment report and architecture decision, with prototype limitations. No automatic production adoption.
In a pipeline, use the stage contract and return to the integrating controller. Run only this specialist's owned scope; preserve the user's accepted decisions and existing authorization.
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.