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-failure-classificationgit 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-failure-classification)<a href="https://agentmods.dev/skills/vivekkrishna/agentic-validation-skills/cige-failure-classification"><img src="https://agentmods.dev/badge/skills/vivekkrishna/agentic-validation-skills/cige-failure-classification.svg" alt="Measured on agentmods" 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 | $0.01318 |
| Opus 5 | $0.00000 | $0.00659 |
| Sonnet 5 | $0.00000 | $0.00264 |
| Haiku 4.5 | $0.00000 | $0.00132 |
Grade A, and why
cige-failure-classification 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 8d 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 — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CIGE: Failure Classification (Dispatcher)
Use this skill immediately after any CIGE test run completes — pass or fail — and before any repair action is taken. It classifies the outcome and names which skill, if any, is allowed to act on it. Classification is not optional and not skippable: no agent may repair a test it has not been dispatched to.
When to invoke
- A test run just finished, regardless of result
- You are deciding whether a "pass" was actually a false positive
- You need to know which self-healing skill is allowed to touch a given failure
For the CIGE format itself, see cige-test-authoring. This skill only decides what happens after a run.
The Decision Flow
This mirrors the CIGE runtime workflow: reveal minimal context → run execution with guardrails → classify → repair → replay → human review → commit.
Run execution with guardrails
│
▼
Failure? ──No──▶ False Positive? ──No──▶ Store evidence, mark pass
│ │
Yes Yes
│ │
▼ ▼
Classify failure Dispatch to cige-stale-execution-repair
│ (Mode B — guardrail strengthening)
│
┌────┼────────────────┐
▼ ▼ ▼
Infra Outdated Product
Fail Test Logic Defect
│ │ │
▼ ▼ ▼
cige- cige-stale- cige-product-
environ execution- defect-
ment- repair (Mode A) escalation
recovery
│ │ │
└────┴────────────────┘
│
▼
Replay in isolated environment
│
▼
Human review and commit
A false positive — the run reports pass, but the pass doesn't hold up (a shortcut satisfied the letter of Execution without the evidence Guardrails actually require) — is checked even when there was no Failure. Don't skip this check just because the run looked clean.
Classifying a Failure
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.
- 8d ago First seen · 108 lines · 0 tokens per session scan A a62ad3519609
cige-failure-classification is a skill published in the GitHub repository vivekkrishna/agentic-validation-skills (1 stars, last pushed 16d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,318 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
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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.
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.
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.