Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add vivekkrishna/agentic-validation-skills --skill cige-test-authoringgit clone --depth 1 https://github.com/vivekkrishna/agentic-validation-skillsWrote 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/vivekkrishna/agentic-validation-skills/cige-test-authoring)<a href="https://agentmods.dev/skills/vivekkrishna/agentic-validation-skills/cige-test-authoring"><img src="https://agentmods.dev/badge/skills/vivekkrishna/agentic-validation-skills/cige-test-authoring/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/vivekkrishna/agentic-validation-skills/cige-test-authoring"><img src="https://agentmods.dev/badge/skills/vivekkrishna/agentic-validation-skills/cige-test-authoring.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00000 | $0.03007 |
| Opus 5 | $0.00000 | $0.01503 |
| Sonnet 5 | $0.00000 | $0.00601 |
| Haiku 4.5 | $0.00000 | $0.00301 |
Grade A, and why
cige-test-authoring 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 9d 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 — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CIGE: Agentic Test Case Authoring
Use this skill when writing, reviewing, or refactoring AI agent test cases. It enforces the CIGE standard — a structured format that separates stable test intent from adaptive execution, enabling self-healing agentic tests.
When to invoke
- Authoring a new agentic test case from scratch
- Reviewing an existing test for brittleness or missing structure
- Designing test guardrails for a new agent workflow
For a completed run — pass or fail — do not decide repairs here. Invoke cige-failure-classification first; it classifies the outcome and names which skill (if any) should act.
The CIGE Format
Every agentic test case must be expressed in this structure:
{
"Context": {
"system": "<app or service under test, version if relevant>",
"environment": "<staging | dev | ephemeral | ...>",
"tools": ["<tool 1>", "<tool 2>"],
"preconditions": ["<seed data>", "<auth state>", "<feature flags>"],
"specRef": "<path or URL to the BRD / product spec that defines expected behavior>",
"buildRef": "<pointer to the build/version under test and its release documentation — changelog, release notes, or build manifest>"
},
"Intent": "<single outcome-based objective — what success looks like>",
"Guardrails": [
"<constraint the agent must never violate>",
"<scope boundary or irreversibility limit>"
],
"Execution": [
"<adaptive step 1 — guidance, not script>",
"<adaptive step 2>",
"<verification: confirm intent was achieved>"
]
}
specRef is required. It is the ground truth that self-healing agents use to distinguish a product defect from an intentional product change. Without it, failure classification cannot be completed.
buildRef is required for the same reason: specRef alone can tell you what the product should do, but not whether the build under test actually contains that behavior yet. Without buildRef, a product-defect classification can't safely conclude "intentional change" — see cige-product-defect-escalation.
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.
- 9d ago First seen · 223 lines · 0 tokens per session scan A fe1c9d90e749
cige-test-authoring is a skill published in the GitHub repository vivekkrishna/agentic-validation-skills (1 stars, last pushed 17d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 3,007 tokens. 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.
Other skills, from other repositories
phx-work
Execute Elixir/Phoenix plan tasks with progress tracking. Use after phx-plan to implement features with mix compile and mix test verification after each step, or --continue to resume interrupted work.
lab:autoresearch
Self-improving loop for plugin skills. Reads program.md, proposes one mutation per iteration, evaluates against deterministic scorer, keeps improvements via git, reverts failures. Targets weakest skill+dimension. Use with /loop for overnight runs.
codex-loop
Fix Elixir/Phoenix code until Codex CLI review comes back clean — bounded review, fix, verify loop before opening a PR. Use when codex is installed and you want an external cross-model critic on your changes before pushing.
mix-compression
Reduce mix output noise (5-15% token savings) by installing rtk filters that compress mix test/credo/dialyzer/compile output before it reaches Claude. Use when long mix output floods context.
verify
Verify Elixir/Phoenix changes — compile, format, and test in one loop. Use after implementation, before PRs, or after fixing bugs.
codex-ab
Run an A/B codex review experiment — holistic codex review vs 3 focused dimension passes (security, ecto, liveview) on the branch diff, classify findings, report a panel-value verdict. Use when the branch is fresh, before any codex review runs.