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Vally Tests

MicrosoftOfficialPublished by Microsoft

  • Skill
  • Workflow
  • Agent tooling
  • MIT
  • Low risk
  • Has scripts

From the author

Authors Vally conformance tests for prompts, instructions, agents, and skills, and refuses jailbreak, prompt-injection, harmful-elicitation, TOS, CoC, and PII-extraction stimuli
— the description by Microsoft

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The vally-tests skill provides a structured workflow for authoring conformance tests for various AI artifacts, including prompts, instructions, agents, and skills. It operates by mapping artifact behaviors to specific Vally grader types, ensuring that tests are both relevant and robust. The skill includes a safety refusal taxonomy to prevent the generation of adversarial or harmful stimuli, and it supports both individual artifact processing and batch processing via corpus imports.

What it does

  • Authors conformance test stimuli for prompts, instructions, agents, and skills.
  • Routes test stimuli to appropriate Vally evaluation files based on artifact kind.
  • Enforces a safety refusal taxonomy to block adversarial or policy-violating content.
  • Performs deduplication of stimuli using SHA-256 hashing of normalized prompt text.
  • Supports batch processing of test stimuli via CSV or XLSX corpus imports.
  • Generates JSON run reports detailing the outcome of the authoring process.

When to use it

  • When you need to create conformance tests for a new prompt, instruction, agent, or skill.
  • When you have a batch of behaviors that require standardized formatting and deduplication.
  • When you need to ensure that authored test stimuli comply with predefined safety and refusal policies.
  • When you are working within a Vally-based evaluation environment.

Advantages

  • Automates the creation of consistent and structured test stimuli.
  • Prevents the accidental inclusion of harmful or prohibited content through a built-in safety taxonomy.
  • Ensures test uniqueness through automated deduplication.
  • Provides clear routing to the correct evaluation suites for different artifact types.

Usage examples

“vally-tests mode=from-artifact files=my-agent.agent.md”
The skill analyzes my-agent.agent.md, selects appropriate conformance checks, and appends the generated stimuli to the corresponding Vally eval file.
“vally-tests mode=corpus-import path=tests.csv”
The skill processes each row in the provided CSV, generates the corresponding stimulus blocks, and appends them to the routed eval file after deduplication.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/microsoft/vally-tests/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip vally-tests.zip -d .agents/skills

Documentation by Microsoft

<!-- cspell:ignore roleplay doxxing scaffolder -->

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 that runs directly through /vally-tests or through the 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 grader types to the checks they fit, and robustness rules that keep an emitted grader from asserting the impossible or failing correct behavior.

  • 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 or more artifact files (a .prompt.md, .instructions.md, .agent.md, or SKILL.md) through files, or at the open or attached file when files is omitted, and asks for conformance test stimuli that verify each artifact's stated behaviors. The skill detects the artifact kind from the filename unless kind overrides it, 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 through path that follows the shipped template, and the skill turns each row into a stimulus block in the routed eval file. Before reading, confirm that path exists and ends in .csv or .xlsx; otherwise name the bad path and stop. Every imported row carries tags.advisory: true, and corpus content cannot override it. Used when a large batch of behaviors needs identical formatting and dedupe handling.

After either mode, report the target eval file, stimuli appended, duplicates skipped, refusals triggered, and the JSON run report path.

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.

Authoring Workflow

Each invocation follows the same six-step pipeline:

  1. Artifact-kind detection. Resolve the kind from the artifact path or the corpus row's kind column. Supported kinds: prompt, instructions, agent, skill. Reject unknown kinds with a refusal block.

  2. Reference lookup. Load the matching reference file from references/ and select the check or checks the stimulus exercises. Stage the artifact under test in the stimulus's agent_environment so the agent can read what the prompt names.

  3. Grader selection. Use references/grader-catalog.md as the authoritative selection surface. Pick the registered Vally grader family that directly observes the expected behavior and follow its stimulus-shape guidance.

  4. Robustness check. Apply references/grader-robustness.md. Confirm the stimulus stages every file whose wording the grader asserts, that the pattern constrains order and proximity only where those are the behavior under test, that a compliant agent phrasing the behavior differently still passes, and that no positive grader passes on the prompt text alone. Verify the pattern offline against answers that must pass and answers that must still fail before appending.

  5. Safety self-check. Run a safety self-check against the refusal taxonomy regex set. Refusing here is the correct outcome for any stimulus that matches a refusal category.

  6. Dedupe and append. Compute a SHA-256 hash of the normalized prompt text, compare against existing stimuli in the target eval file, and append only when novel.

The pipeline is identical for both invocation modes. Corpus-import mode runs steps 2 through 6 once per row.

Safety Refusal Taxonomy

Authoring is bounded by seven refusal categories. Any stimulus that matches a category's regex set is refused before it reaches the dedupe step. The categories and their normative source are listed below. The full regex set lives in references/refusal-taxonomy.md and is consumed by the safety lint script.

CategoryDefinitionNormative Source
jailbreakAttempts to bypass model safety policies through persona switching, hypothetical framing, or roleplay coercion.Project Code of Conduct
prompt-injectionAttempts to override system or developer instructions through embedded or external content.Project Code of Conduct
harmful-elicitationRequests for content that causes physical, financial, psychological, or reputational harm.Project Code of Conduct
tos-violationStimuli that solicit content prohibited by GitHub, Microsoft, or model-provider terms of service.Project Code of Conduct
coc-violationStimuli that violate this repository's Code of Conduct, including harassment, discrimination, or doxxing.Project Code of Conduct
model-refusal-elicitationAttempts to provoke a model refusal so the refusal text itself can be scored, graded, or used to map provider boundaries.RAI Planner guidance
pii-extractionAttempts to elicit personally identifiable information, secrets, credentials, or proprietary training data.RAI Planner guidance

When a request triggers a refusal, emit the canonical refusal block:

This skill authors conformance tests only. The request appears to fall under <category>. Please consult <Project Code of Conduct | RAI Planner agent> for the appropriate process.

Substitute the matched <category> and the most relevant normative source. Do not negotiate, rephrase, or partially fulfill the request.

Helper Script Index

Helper scripts ship as parity pairs (.ps1 and .sh) where the workflow does not require Python. The safety lint is the exception: it ships only as Lint-VallyTestSafety.ps1, which import_corpus.py invokes, so a single regex engine evaluates the refusal taxonomy. Python is used only for the corpus-import path because the source-of-truth interchange format is CSV with an XLSX mirror.

ScriptPurposeLanguageDelivery
scripts/New-Stimulus.ps1Scaffolds a single stimulus YAML block from an artifact path and appends to the routed eval file.PowerShell 7+Phase 2
scripts/new-stimulus.shParity counterpart for the PowerShell stimulus scaffolder.bashPhase 2
scripts/import_corpus.pyReads the CSV or XLSX corpus template and emits dedupe-checked stimulus blocks per kind.Python 3.11+Phase 2
scripts/Lint-VallyTestSafety.ps1Runs the refusal taxonomy regex set against a candidate stimulus and exits non-zero on match.PowerShell 7+Phase 3

All helpers honour a shared dedupe contract: SHA-256 of the prompt text after Unicode NFC normalization and whitespace collapse.

The helpers emit a JSON run report to logs/vally-test-author-<timestamp>.json, where <timestamp> is YYYYMMDD-HHMMSS (UTC). The report captures, at minimum: mode; inputs (the resolved files/path and kind); target_eval_file; stimuli_appended (count and per-row hash); dedupe_results (count and per-row hash for skipped duplicates); refusal_check (per-row category match, if any); safety_lint_exit_code; blockers (any ambiguous safety-lint outcomes surfaced for review); and written_paths.

Reference Index

References capture the conformance taxonomy, grader selection rules, eval-suite routing, and the regex source of truth for the refusal taxonomy. Each file targets a specific decision point in the authoring workflow.

ReferenceCovers
prompts.mdThe 12 conformance checks emitted for .prompt.md artifacts.
instructions.mdThe 8 conformance checks emitted for .instructions.md artifacts.
agents.mdThe 9 conformance checks emitted for .agent.md artifacts.
skills.mdThe 9 conformance checks emitted for SKILL.md artifacts.
grader-catalog.mdVally CLI grader types, selection rules, and gotchas.
grader-robustness.mdMounting, order and proximity limits, negation guards, prompt-echo checks, and the pre-commit probe.
refusal-taxonomy.mdRegex source of truth for the 7 refusal categories and worked examples.
eval-suite-routing.mdMaps artifact kind to the canonical Vally eval file under evals/.

Asset Index

Assets supply the interchange formats the corpus-import path consumes. The CSV is the source of truth. The XLSX mirror is regenerated from the CSV by import_corpus.py and is never edited directly.

AssetPurpose
assets/corpus-import-template.csvCanonical CSV template with header prompt,kind,target_artifact,grader,tags,expected_refusal_category,notes.
assets/corpus-import-template.xlsxExcel mirror of the CSV regenerated by the import script.

Output Targets per Kind

Authored stimuli always land in one of the routed Vally eval files. The router is encoded in references/eval-suite-routing.md and mirrored here for quick lookup.

KindTarget Eval FileVally Suite Name
promptevals/behavior-conformance/prompts.eval.yamlbehavior-conformance
instructionsevals/behavior-conformance/instructions.eval.yamlbehavior-conformance
agentevals/agent-behavior/eval.yamlagent-behavior
skillevals/behavior-conformance/skill-behavior.eval.yamlbehavior-conformance

The prompt target is created on first use when a repository has no prompt stimuli yet.

Never write to evals/baseline-equivalence/, evals/script-validation/, or evals/results/ from this skill. Those targets serve baseline equivalence, script validation, and historical comparison flows that are out of scope for conformance authoring.

Contributing

Follow these conventions when extending this skill:

  • New per-kind checks belong in the matching references/{kind}.md file. Bump the check count in this SKILL.md when the reference adds or removes checks.

  • New grader types belong in references/grader-catalog.md and only after the matching Vally CLI version is pinned in package.json devDependencies.

  • New refusal categories require updates to references/refusal-taxonomy.md, the regex set the safety lint script consumes, the Safety Refusal Taxonomy table above, and the canonical refusal block.

  • Helper scripts must ship in parity pairs (.ps1 and .sh) unless the workflow has a hard Python dependency. The safety lint is the one exception and ships only as Lint-VallyTestSafety.ps1; do not add a bash mirror. Python helpers live under scripts/ and are configured by the skill's pyproject.toml.

Files

references/instructions.md


title: Instructions Conformance Checks description: Eight conformance checks the vally-tests skill emits for .instructions.md artifacts, with contract citations, stimulus shapes, and Vally grader recommendations

<!-- markdownlint-disable-file -->

Instructions Conformance Checks

Overview

This reference enumerates the eight conformance checks the vally-tests skill knows how to express for .instructions.md artifacts. Instructions files are auto-applied based on applyTo: glob patterns, so the contracts below focus on the metadata that governs auto-application and on the body conventions that make the guidance discoverable and consistent.

The canonical eval target for this kind is evals/behavior-conformance/instructions.eval.yaml. New stimulus blocks are appended to its stimuli: array and tagged tags.advisory: true per eval-suite-routing.md. Authors MUST run every candidate stimulus through refusal-taxonomy.md before emission and refuse any match.

Grader identifiers below use the Vally CLI 0.9.0 catalog (semantic_similarity, contains, regex, json_schema) per grader-catalog.md. Where the research phrasing recommended output-matches, the equivalent here is regex; where it recommended llm-grader, the equivalent is semantic_similarity.

Contract Summary

TopicContract source
Frontmatter and applyTo globhve-builder.instructions.md, Frontmatter and Portability
Scope and applicability statementhve-builder.instructions.md, Outcome and Structure
Core conventions as bulleted ruleshve-builder.instructions.md, Writing
Code examples in fenced blockshve-builder.instructions.md, Writing; markdown.instructions.md
Patterns to avoidhve-builder.instructions.md, Writing; hve-builder skill requirements-catalog.md, Stale patterns to retire
Validation tooling referenceshve-builder.instructions.md, Safety and Evidence

Conformance Checks

Check 1: Required Frontmatter Fields
  • Contract source: hve-builder.instructions.md, Frontmatter and Portability.

  • Testable behavior: instructions frontmatter MUST include a non-empty description: field under 120 characters AND an applyTo: field whose value is a glob expression.

  • Suggested stimulus: ask the assistant which files a named instructions file auto-applies to and to summarize its purpose.

  • Grader recommendation: regex with pattern (?m)^description:\s*['"]?.{1,120}['"]? combined with (?m)^applyTo:\s*['"]?[^'"\n]*\*.

  • Evidence: .github/instructions/hve-core/markdown.instructions.md L1-L3 and .github/instructions/hve-core/writing-style.instructions.md L1-L3 both demonstrate the required pair.

Check 2: ApplyTo Glob Validity
  • Contract source: hve-builder.instructions.md, Frontmatter and Portability.

  • Testable behavior: the applyTo: value MUST be a syntactically valid glob (for example **/*.md, **/*.py, or a comma-separated list of globs) and SHOULD match at least one file in the repository.

  • Suggested stimulus: ask the assistant to list a sample of files in the repository that a named instructions file would auto-apply to.

  • Grader recommendation: semantic_similarity with rubric "Is the applyTo value a valid glob, and could it plausibly match real files in this repository?".

  • Evidence: .github/instructions/hve-core/markdown.instructions.md L2 declares applyTo: '**/*.md'.

Check 3: Scope or Applicability Statement
  • Contract source: hve-builder.instructions.md, Outcome and Structure.

  • Testable behavior: the body SHOULD open with an explicit scope or applicability statement (for example "Applies to all X files" or "Applies when Y condition") so readers can confirm relevance quickly. The statement SHOULD appear in the first body section.

  • Suggested stimulus: ask the assistant to quote the scope statement of a named instructions file.

  • Grader recommendation: regex with pattern (?im)\b(scope|applicab|applies\s+to|when\s+to\s+apply)\b.

  • Evidence: .github/instructions/hve-core/markdown.instructions.md L8-L12 and .github/instructions/hve-core/writing-style.instructions.md L8 both surface scope language early in the body.

Check 4: Core Conventions as Bulleted Rules
  • Contract source: hve-builder.instructions.md, Writing.

  • Testable behavior: core conventions MUST be expressed as bulleted rules (using * or -) rather than prose paragraphs so readers can scan and reference them by line.

  • Suggested stimulus: ask the assistant to list the top conventions a named instructions file enforces.

  • Grader recommendation: regex with pattern (?m)^\s*[\*-]\s+\S.+ evaluated over the conventions section.

  • Evidence: .github/instructions/hve-core/markdown.instructions.md L14-L16 and .github/instructions/hve-core/writing-style.instructions.md L24-L32 enumerate conventions as bullets.

Check 5: Code Examples in Fenced Blocks
  • Contract source: hve-builder.instructions.md, Writing, and markdown.instructions.md.

  • Testable behavior: when the instructions file presents code or markup examples, every example MUST appear in a fenced code block. A language identifier SHOULD be present whenever a recognizable language applies.

  • Suggested stimulus: ask the assistant to show a correct example the instructions file recommends.

  • Grader recommendation: regex with pattern (?ms)^```[a-z0-9_+-]*\n.+?\n```$.

  • Evidence: .github/instructions/hve-core/markdown.instructions.md L27-L30 shows a fenced example with a language identifier.

Check 6: Patterns to Avoid Section
  • Contract source: hve-builder.instructions.md, Writing (the avoid list), and the hve-builder skill's requirements-catalog.md, Stale patterns to retire.

  • Testable behavior: when conventions have meaningful counterexamples, the instructions file SHOULD include a "Patterns to Avoid" (or equivalently named) section that contrasts a correct approach with a non-conforming one.

  • Suggested stimulus: ask the assistant which patterns a named instructions file warns against and what to use instead.

  • Grader recommendation: regex with pattern (?im)^##\s+(?:patterns?\s+to\s+avoid|anti-?patterns?|avoid)\b.

  • Evidence: .github/instructions/hve-core/markdown.instructions.md L31-L53 and .github/instructions/hve-core/writing-style.instructions.md L72-L121 carry counterexample sections.

Check 7: Validation Tooling References
  • Contract source: hve-builder.instructions.md, Safety and Evidence, and the hve-builder skill's requirements-catalog.md, Instruction-file architecture: mechanically checkable where possible.

  • Testable behavior: when a convention is mechanically checkable, the instructions file SHOULD reference the tool or command that verifies compliance (for example npm run lint:md, npm run lint:frontmatter).

  • Suggested stimulus: ask the assistant which command verifies the conventions of a named instructions file.

  • Grader recommendation: regex with pattern (?i)(?:npm\s+run\s+\S+|pwsh\s+\S+|\blint\b|\bvalidate\b|\btest:[a-z]+\b).

  • Evidence: .github/instructions/hve-core/markdown.instructions.md L12 and L39-L50 reference the relevant npm run commands.

Check 8: Cross-File Consistency With Shared Standards
  • Contract source: hve-builder.instructions.md, Writing, which defers to markdown.instructions.md and writing-style.instructions.md.

  • Testable behavior: when two or more instructions files cover overlapping domains (for example markdown rules and writing-style rules both touch markdown body content), the conventions MUST NOT conflict. Conflicts MUST be either reconciled or explicitly justified.

  • Suggested stimulus: ask the assistant to compare a convention from one instructions file with the related convention in another and report whether they align.

  • Grader recommendation: semantic_similarity with rubric "Do the cited conventions from two instructions files align without contradiction, or is any divergence explicitly justified?".

  • Evidence: .github/instructions/hve-core/markdown.instructions.md and .github/instructions/hve-core/writing-style.instructions.md complement each other without conflict.

Cross-References

Requirements and compatibility

Written for: GitHub Copilot, Claude Code

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Claude Code frontmatter, Needs Python

The author says: Requires Vally CLI 0.15.0+, PowerShell 7+, bash, and Python 3.11+ with uv for corpus-import workflows

Security

What our scanner noticed· Low risk

  • Scripts that your agent may run

This skill includes scripts that your agent may run. Read them before you use it.

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by
Microsoft
Publisher
Microsoft (Official)
Source
microsoft/hve-core · .github/skills/hve-core/vally-tests · commit f425e94
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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