Skip to main content
Glama

generate_adversarial_probes

Generates concrete adversarial test probes per workflow, specifying failure scenarios and invariants for validation before merging.

Instructions

Generates concrete Tier-3 adversarial test directives per affected workflow. Each probe is a specific failure scenario plus the invariant that must hold — not a vague 'add more tests' nudge. Categories: concurrency (visibility-timeout races, write-write conflicts), idempotency (same request twice within 500ms), retry storms (50 redeliveries of same event id), replay (24-hour-old signed payload), partial failure (worker crashes after side effect before ack), cache stampede (mass expiry → thundering herd), and ordering (out-of-order event arrival). Probes are domain-aware — Payments probes are different from Caching probes. Use this to brief an agent on what to actually run against a PR before merging.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Despite no annotations, the description clearly explains behavior: generates probes with specific failure scenarios and invariants, is domain-aware, and does not indicate side effects. Could mention that it does not modify state or require auth, but it covers essential traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with front-loaded purpose, categorized examples, and usage context. Each sentence adds value; slightly verbose but within reason.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given zero parameters and no output schema, description covers purpose, categories, and usage thoroughly. Provides enough context for an agent to decide when and why to call this tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema has zero parameters with 100% coverage, so schema already fully describes input. Description does not need to add param info; baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the tool generates concrete Tier-3 adversarial test directives per affected workflow, listing specific categories (concurrency, idempotency, etc.) and distinguishing from vague test suggestions. The purpose is specific and distinct from sibling tools like generate_verification_plan.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly instructs to use before merging a PR ('to brief an agent on what to actually run against a PR before merging'). Does not explicitly state when not to use or contrast with siblings, but context implies proper usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/vighriday/Veris'

If you have feedback or need assistance with the MCP directory API, please join our Discord server