agentic-validation-skills: Instructions file for Claude Code

CLAUDE.md

agentic-validation-skills CLAUDE.md is an instructions file for Claude Code from vivekkrishna/agentic-validation-skills. It costs 1,635 tokens per session, scanned A, original, Apache-2.0.

A set of instructions for testing AI agents using four ideas: context, intent, guardrails, and execution. It says to define the system and environment, test the intended outcome, set safety limits, and adapt execution when needed.

In plain words
What is it for?
Use it when writing or running tests for AI agents, especially tests that must remain useful as the interface or implementation changes.
Why use it?
It reduces tests based on missing assumptions, unclear goals, or unsafe actions, which can lead to flaky or misleading results.

Instructions file for Claude Code

Written for Claude Code: the file is CLAUDE.md.

This is vivekkrishna/agentic-validation-skills's own configuration. It tells Claude Code how to work on agentic-validation-skills itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything agentic-validation-skills configures →

Reuse

Borrowing it

Nothing to install: this file belongs to vivekkrishna/agentic-validation-skills. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/vivekkrishna/agentic-validation-skills/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/vivekkrishna/agentic-validation-skills

Made for: Claude Code.

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README.md
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Per session 1,635 This file is loaded in full into every session.
When invoked 1,635 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.01635 $0.01635
Opus 5 $0.00817 $0.00817
Sonnet 5 $0.00327 $0.00327
Haiku 4.5 $0.00163 $0.00163

Measured 6d ago against content hash d1f9042410bc, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

agentic-validation-skills CLAUDE.md 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 6d 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.

CLAUDE.md · 119 lines

How it starts

The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agentic Test Automation Guidelines (CIGE)

Behavioral guidelines for authoring and executing agentic AI test cases. Based on the CIGE standard: Context, Intent, Guardrails, Execution.

Tradeoff: These guidelines bias toward safety and goal fidelity over speed. For trivial assertions, use judgment.

1. Establish Context Before Testing

Narrow the agent's decision space. Never test into the void.

Before writing or executing any test:

  • Declare the system under test explicitly: what app, environment, version, and precondition state?
  • Specify what tools and APIs the agent has access to.
  • State environmental assumptions: auth state, seed data, feature flags, dependent services.
  • If context is ambiguous, ask — do not assume defaults and run.

Context that is missing or vague leads to wasted exploration, flaky results, and unpredictable agent behavior.

2. Anchor Every Test to Intent

Intent is the stable core. Never collapse it into steps.

When defining or analyzing a test:

  • Write intent as an outcome, not a procedure: "User can complete checkout" — not "Click button, fill form, click submit."
  • Intent must survive: UI changes, infrastructure migrations, workflow refactors.
  • Ask: "What is the agent trying to confirm?" — that is the intent. Everything else is execution guidance.
  • Separate intent from execution in every test definition. Never merge them.

The test: Can you state what this test is verifying in one outcome-focused sentence? If not, the intent is buried in the steps.

3. Define Guardrails Before Executing

Bounded autonomy is safe autonomy. No guardrails = no execution.

Before any agent runs a test:

  • Declare what the agent must NOT do: no production mutations, no irreversible operations, no sensitive data exposure.
  • Specify scope boundaries: which environments, data ranges, and services are off-limits.
  • If an execution path would violate a guardrail, stop and surface it — never route around it.
  • Guardrails are constraints, not suggestions. They define the difference between a test run and an incident.

Read the full file on GitHub · 119 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. 6d ago First seen · 119 lines · 1,635 tokens per session scan A d1f9042410bc

Subscribe to this mod's changes

agentic-validation-skills CLAUDE.md is an instructions file published in the GitHub repository vivekkrishna/agentic-validation-skills (1 stars, last pushed 14d ago), licensed Apache-2.0. It adds 1,635 tokens to every session, about $0.0082 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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