vally-tests

vally-tests is a skill for Claude Code, Codex from microsoft/hve-core. It costs 47 tokens per session (2,474 once invoked), scanned A, original, MIT.

A tool for writing conformance tests for prompts, instruction files, agents, and skills. These tests check whether an artifact follows behaviors it already claims to support.

In plain words
What is it for?
Use it to create Vally tests for documented behaviors, including appropriate refusals for jailbreak, prompt-injection, harmful, policy, and personal-data extraction scenarios.
Why use it?
An agent artifact may look correct while failing in real use or responding unsafely to certain inputs. Conformance tests make those failures easier to identify and explain.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/microsoft/hve-core/vally-tests
Any agent
npx skills add microsoft/hve-core --skill vally-tests
Clone the repo
git clone --depth 1 https://github.com/microsoft/hve-core

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for vally-tests

README.md
[![agentmods](https://agentmods.dev/badge/skills/microsoft/hve-core/vally-tests.svg)](https://agentmods.dev/skills/microsoft/hve-core/vally-tests)
Your own site
<a href="https://agentmods.dev/skills/microsoft/hve-core/vally-tests"><img src="https://agentmods.dev/badge/skills/microsoft/hve-core/vally-tests.svg" alt="Measured on agentmods" height="20"></a>
Per session 47 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,474 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00047 $0.02474
Opus 5 $0.00023 $0.01237
Sonnet 5 $0.00009 $0.00495
Haiku 4.5 $0.00005 $0.00247

Measured 3d ago against content hash c6c3ed43c2f1, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

vally-tests 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 3d ago.

The scan reads SKILL.md. This mod also ships 14 executable files (scripts/import_corpus.py, scripts/lint-vally-test-safety.sh, scripts/Lint-VallyTestSafety.ps1, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

.github/skills/hve-core/vally-tests/SKILL.md · 138 lines

How it starts

The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Vally Tests Skill

Purpose

This skill authors Vally conformance tests for the four supported artifact kinds in this repository: prompts, instructions, agents, and skills. Each test exercises a documented behavior the artifact already claims and routes the result through an appropriate Vally grader so failures are explainable. Test authoring is bounded by a refusal taxonomy that keeps the skill out of adversarial, harmful, or policy-evasion territory.

Follow the shared content-policy public-output guard for eval stimuli and any public summaries derived from this skill. Vally tests are not a venue for terms-of-service boundary mapping, payload generation, refusal-text scoring, hidden-instruction disclosure, PII extraction, or secret extraction.

The skill ships:

  • A canonical authoring workflow used by the Vally prompts and Vally Test Author subagent.
  • Per-kind reference files that enumerate every conformance check the skill knows how to express.
  • A grader catalog that maps Vally CLI 0.9.0 grader types to the checks they fit.
  • A safety refusal taxonomy with regex patterns the safety lint script consumes.
  • Helper scripts and asset templates for stimulus emission, corpus import, and dedupe.

When to Invoke

Invoke this skill in one of two modes:

  • From-artifact mode. The caller points at one artifact file (a .prompt.md, .instructions.md, .agent.md, or SKILL.md) and asks for conformance test stimuli that verify the artifact's stated behaviors. The skill detects the artifact kind from the filename, looks up the matching per-kind reference, picks graders, and appends stimulus blocks to the routed Vally eval file.
  • Corpus-import mode. The caller supplies a CSV or XLSX corpus that follows the shipped template, and the skill turns each row into a stimulus block in the routed eval file. Used when a large batch of behaviors needs identical formatting and dedupe handling.

Do not invoke this skill to:

  • Generate adversarial probes, jailbreak attempts, prompt-injection payloads, or red-team stimuli.
  • Test refusal quality on harmful, illegal, or policy-violating prompts.
  • Author stimuli that elicit PII, secrets, hidden instructions, or model self-disclosure.
  • Store payload examples, paraphrased prohibited requests, or quoted flagged content in Vally eval specs, corpus rows, PR summaries, issue bodies, or comments.
  • Replace Responsible AI threat modeling. RAI work lives in the RAI Planner agent.

Read the full file on GitHub · 138 lines

Changes

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.

  1. 3d ago First seen · 138 lines · 47 tokens per session scan A c6c3ed43c2f1

Subscribe to this mod's changes

vally-tests is a skill published in the GitHub repository microsoft/hve-core (1,422 stars, last pushed today), licensed MIT. It adds 47 tokens to every session and 2,474 once invoked, about $0.0002 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 2026-08-30.

Related

Other skills, from other repositories

instrument-data-to-allotrope

Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…

anthropics/knowledge-work-plugins · 123 tokens

agent-platform-model-registry

Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.

google/skills · 60 tokens

html-ppt-hermes-cyber-terminal

OpenDesign + BYOK: choosing and wiring your own model, hands-on — cost, quality, and the routing decision. Built as a decision-grade AI literacy deck for engineers, IT, applied-AI teams.

nexu-io/open-design · 53 tokens

foundry-config-setup

Resolve missing setup caused by a hardcoded Foundry project endpoint or model in a sample. Use when a sample fails because it uses a placeholder/hardcoded projectendpoint (for example "https://your-project.services.ai.azure.com") or a hardcoded model instead of reading them from the environment.

microsoft/agent-framework · 65 tokens

auditing-subgroup-fairness

Audit an OpenMed NER or de-identification model for performance disparities across demographic subgroups (sex, age band, race/ethnicity when available) using openmed.eval.fairnessreport. Use when the user wants per-subgroup recall and leakage, wants to check whether de-identification under-protects a group, wants to…

maziyarpanahi/openmed · 148 tokens

aatmf-t10-confidentiality-breach

AATMF T10 — Integrity & Confidentiality Breach. System prompt extraction, training-data extraction, model-weight leakage, private-key recovery.

PurpleAILAB/Decepticon · 39 tokens