Borrowing it
Nothing to install: this file belongs to openshift/lightspeed-agentic-operator. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/openshift/lightspeed-agentic-operator/main/.cursor/skills/validate-and-fix/SKILL.mdgit clone --depth 1 https://github.com/openshift/lightspeed-agentic-operatorWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/openshift/lightspeed-agentic-operator/validate-and-fix)<a href="https://agentmods.dev/skills/openshift/lightspeed-agentic-operator/validate-and-fix"><img src="https://agentmods.dev/badge/skills/openshift/lightspeed-agentic-operator/validate-and-fix/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/openshift/lightspeed-agentic-operator/validate-and-fix"><img src="https://agentmods.dev/badge/skills/openshift/lightspeed-agentic-operator/validate-and-fix.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00057 | $0.00810 |
| Opus 5.5 | $0.00023 | $0.00324 |
| Sonnet 5.5 | $0.00011 | $0.00162 |
| Haiku 4.5 | $0.00006 | $0.00081 |
Grade A, and why
validate-and-fix scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Validate & Auto-Fix
Run the project validation pipeline, auto-fix trivial issues, and re-run until green or a real failure is found.
Rules
- This repository has no root Makefile for tests; use
go test ./...from the repo root (not operator Makefile conventions from other repos). - Never modify production logic to fix a test. Only fix test expectations, imports, formatting.
- Never skip or delete a failing test.
- Stop after 3 auto-fix cycles to avoid loops.
- Report real failures clearly; do not attempt speculative fixes.
Step 1: Run Unit Tests
go test ./... -count=1 2>&1 | tail -80
If all pass, proceed to Step 3 (vet / fmt). If failures occur, classify each failure (see Step 2).
Step 2: Classify and Fix Failures
For each failure, determine its type:
Auto-fixable (fix immediately, then re-run Step 1):
| Type | Fix |
|---|---|
| Test expects old constant value | Update assertion to match new value |
| Test uses renamed function | Update function name in test |
| Import error from refactor | Update import path |
| Missing cleanup in test | Add cleanup or use existing cleanup helpers |
Real failures (do not auto-fix):
- Logic errors in production code
- Assertion failures reflecting actual behavior regressions
- Reconciliation loop failures
- Context cancellation issues
- Failures in code you did not modify
For real failures: report the test name, file, error message, and stop.
Step 3: go vet and formatting
go vet ./... 2>&1 | tail -40
go fmt ./...
Fix straightforward vet issues (unused vars in tests, etc.) and re-run.
Step 4: API module — kube API linter (when API types changed)
If files under api/v1alpha1/ (or other api/ packages) were touched, run the custom kube API linter from the repo root:
golangci-lint custom
cd api && GOWORK=off ../bin/golangci-lint-kube-api-linter run --config ../.golangci-kal.yml ./...
See CLAUDE.md in the repo for details. Fix reported issues or stop if they need design discussion.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 105 lines · 57 tokens per session scan A 27acb20112f7
validate-and-fix is a skill published in the GitHub repository openshift/lightspeed-agentic-operator (15 stars, last pushed today), licensed Apache-2.0. It adds 57 tokens to every session and 810 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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