backend-skill
AGENTS.md0 starsChanged 4 months agoMITView on GitHub
This repository is the released backend skill: the server-side half of the Build stage of the Digital Product Skills family, peer of frontend. The runtime skill lives under skills/backend/; repository and plugin names use the -skill suffix. Version metadata lives in .codex-plugin/plugin.json, CHANGELOG.md, and tags — never in SKILL.md. The running server behind the contract: API/handler implementation (REST/GraphQL/gRPC/tRPC), domain/service-layer logic, OLTP persistence (schema, migrations, transactions, pooling), auth implementation (sessions/JWT, OAuth2/OIDC, RBAC/ABAC/ReBAC), async work and messaging (queues/outbox/saga/idempotency/durable execution), caching and rate…
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 31,774 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 repository13 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- site/llms.txtllms.txt
- mediabunnySkill
- remotion-best-practicesSkill
- remotion-captionsSkill
- remotion-createSkill
- remotion-docsSkill
- remotion-interactivitySkill
- remotion-markupSkill
- remotion-renderSkill
- remotion-saasSkill
- remotion-upgradeSkill
- backendSkill
The file
We split this AGENTS.md into the rules it gives an agent
6 rules. About 0 are common, 1 is distinctive, and 5 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.
5
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 24
Run scripts/check-sync before any release.
- Very specific: line 34
Every method must be grounded in its named source with a citation in SOURCES.md.
- Very specific: line 37
Keep the boundary discipline: reference sibling territory by backtick name and recommend it.
- Very specific: line 39
Keep the eval contract current: evals/{activation,traversal,output,compression-ablation} must reflect the router.
- Very specific: line 41
Treat README as the primary storefront.
- Distinctive: line 48
Do not mark a change complete merely because lint passes.
≈ “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
Agent guide — backend-skill
This repository is the released backend skill: the server-side half of the Build stage of the
Digital Product Skills family, peer of frontend. The runtime skill lives under skills/backend/;
repository and plugin names use the -skill suffix. Version metadata lives in
.codex-plugin/plugin.json, CHANGELOG.md, and tags — never in SKILL.md.
What this skill owns
The running server behind the contract: API/handler implementation (REST/GraphQL/gRPC/tRPC),
domain/service-layer logic, OLTP persistence (schema, migrations, transactions, pooling), auth
implementation (sessions/JWT, OAuth2/OIDC, RBAC/ABAC/ReBAC), async work and messaging
(queues/outbox/saga/idempotency/durable execution), caching and rate limiting, implementing a threat
model's controls (OWASP), outbound service integration (clients/webhooks), and the tests that prove
it runs — across REST-CRUD, serverless/edge, realtime, event-driven-microservices, and agentic
backends in Node/Python/Go/Rust/JVM. It sits between architecture (which decides the boundaries,
contract shape, NFR budgets, and threat model) and operate/quality (which deploy, monitor, and
independently verify). It owns the implementation craft, not the decision behind it. It recommends
siblings (architecture, frontend, data, ai, quality, operate) for work it does not own
and never silently invokes them.
Maintainer rules
- Run
scripts/check-syncbefore any release; it validates packaging, routes, references, metadata, and eval fixtures. Runscripts/lint-skillandscripts/count-skill-tokenstoo. SKILL.mdis the direct router: a faceted table of one primary job × at most one base surface (the agentic overlay stacks additively). References are flat underreferences/, directly linked, self-describing, and loaded only when their observable condition applies. No required second-hop navigation.- Retrieval-first is load-bearing, not a nit: never generate framework/ORM/DB-specific code without fetching the current official docs/types and version-gating idioms to the target release — backends ship breaking changes fast (Prisma 7, Drizzle 1.0, Go 1.22 routing, Kafka 4.0 KRaft-only).
- Every method must be grounded in its named source with a citation in
SOURCES.md. Fix a wrong formula, a misattribution, or a license-posture error (including a datastore product's self-host/resale terms) as a correctness bug, not a nit. - Keep the boundary discipline: reference sibling territory by backtick name and recommend it; never absorb architecture/frontend/data/ai/quality/operate work.
- Keep the eval contract current:
evals/{activation,traversal,output,compression-ablation}must reflect the router. Add near-miss activation cases when a new sibling overlap appears. - Treat README as the primary storefront. The
site/andremotion/profiles follow thesite/README.mddesign brief — designed for this skill's faceted-router model inside the shared family chrome and its own emerald accent, never a filled-in skeleton. - Release through matching plugin version + changelog entry +
v<version>tag + GitHub Release, and keep the GitHub About area configured (family-style description, canonical site alias as homepage, base + domain topics).
Do not mark a change complete merely because lint passes. Activation, traversal, and output evaluations must show the skill still changes agent behavior usefully.
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.

