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-product-defect-escalationgit 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-product-defect-escalation)<a href="https://agentmods.dev/skills/vivekkrishna/agentic-validation-skills/cige-product-defect-escalation"><img src="https://agentmods.dev/badge/skills/vivekkrishna/agentic-validation-skills/cige-product-defect-escalation/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-product-defect-escalation"><img src="https://agentmods.dev/badge/skills/vivekkrishna/agentic-validation-skills/cige-product-defect-escalation.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 | $0.00062 | $0.01035 |
| Opus 5 | $0.00031 | $0.00517 |
| Sonnet 5 | $0.00012 | $0.00207 |
| Haiku 4.5 | $0.00006 | $0.00103 |
Grade A, and why
cige-product-defect-escalation 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 today.
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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CIGE: ProductDefectAgent
Invoked by cige-failure-classification when a run is classified as a Product Defect: execution reached the system under test, the environment is healthy, execution steps are current — but the outcome does not match Intent.
When to invoke
- Execution reached the system under test
- Environment is healthy (ruled out by
cige-failure-classificationas Infrastructure Failure) - Execution steps are current (ruled out as Outdated Test Logic)
- The observed outcome contradicts
Intent
This is also the escalation target when cige-stale-execution-repair (Mode A) cannot find any execution path that satisfies Intent within Guardrails — that usually means the failure was misclassified as stale execution when it's really a defect.
What it does
- Read
Intent(what was expected) and capture actual system behavior (what happened). - Fetch
specRef(the BRD / product spec) andbuildRef(the tested build's release documentation) to determine ground truth. Four cases:
Case A — specRef unchanged, system diverged.
The system broke. This is a confirmed product defect.
→ File a bug report with: Intent, actual behavior, specRef snapshot, execution trace.
→ Do not modify the test definition.
Case B — specRef was recently updated, buildRef's release documentation confirms the tested build actually includes that update, and system behavior matches the new spec.
The product intentionally changed, and this build actually shipped it. The Intent in the test is now stale.
→ Propose an Intent update that aligns with the new specRef.
→ Surface the proposed change for human approval before any write.
→ Guardrails are never touched, even though the spec changed.
A spec being updated and behavior superficially matching it is not sufficient for Case B on its own — the spec could have been edited ahead of the actual release, or the match could be coincidental. Confirming the build correlation via buildRef is what separates Case B from Case D.
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.
- today Changed · +5 lines · +62 tokens per session e563759f5713
- 10d ago First seen · 70 lines · 0 tokens per session scan A 9ba9120504fd
cige-product-defect-escalation is a skill published in the GitHub repository vivekkrishna/agentic-validation-skills (1 stars, last pushed yesterday), licensed Apache-2.0. It adds 62 tokens to every session and 1,035 once invoked, about $0.0003 per session on Opus 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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investigate
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