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platform-backend

Server-side architecture and security — API design, error handling, validation, logging. Use when building APIs, server logic, or reviewing backend security.

Install with Tessl CLI

npx tessl i github:ravnhq/ai-toolkit --skill platform-backend
What are skills?

63

1.06x

Quality

44%

Does it follow best practices?

Impact

99%

1.06x

Average score across 3 eval scenarios

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/platform/platform-backend/SKILL.md
SKILL.md
Review
Evals

Principles

  • Throw early with guard clauses — fail fast at the top of functions
  • Never swallow errors silently — log or propagate every failure

Rules

See rules index for detailed patterns.

Examples

Positive Trigger

User: "Design error handling and validation strategy for this API endpoint."

Expected behavior: Use platform-backend guidance, follow its workflow, and return actionable output.

Non-Trigger

User: "Create a Tailwind design token scale."

Expected behavior: Do not prioritize platform-backend; choose a more relevant skill or proceed without it.

Troubleshooting

Skill Does Not Trigger

  • Error: The skill is not selected when expected.
  • Cause: Request wording does not clearly match the description trigger conditions.
  • Solution: Rephrase with explicit domain/task keywords from the description and retry.

Guidance Conflicts With Another Skill

  • Error: Instructions from multiple skills conflict in one task.
  • Cause: Overlapping scope across loaded skills.
  • Solution: State which skill is authoritative for the current step and apply that workflow first.

Output Is Too Generic

  • Error: Result lacks concrete, actionable detail.
  • Cause: Task input omitted context, constraints, or target format.
  • Solution: Add specific constraints (environment, scope, format, success criteria) and rerun.

Workflow

  1. Identify whether the request clearly matches platform-backend scope and triggers.
  2. Apply the skill rules and referenced guidance to produce a concrete result.
  3. Validate output quality against constraints; if gaps remain, refine once with explicit assumptions.
Repository
ravnhq/ai-toolkit
Last updated
Created

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.