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TrustHarness

TrustHarness

by ofirtro
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_issue

Read a synthetic issue to test AI agent responses to untrusted data in security evaluations.

Instructions

Read an untrusted issue from the synthetic repository.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "issue_number": "<issue_number>"
    },
    "name": "get_issue"
  }
}

Input Schema

NameRequiredDescriptionDefault
issue_numberYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior3/5

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

With no annotations, the description carries the burden for behavioral disclosure. It implies a read-only operation via the verb 'Read' and adds the context of 'untrusted' and 'synthetic repository', but it does not explain any side effects, permissions, or special handling. It offers a basic level of transparency.

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?

The description is a concise single sentence with no filler, front-loaded with the verb 'Read'. It is appropriately sized for a simple tool, though slightly sparse in detail.

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

Completeness2/5

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

The tool lacks annotations and an output schema, so the description should explain the return value and behavior in more detail. It does not mention what is returned (e.g., issue body, metadata) or any error conditions, leaving the agent without essential context.

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

Parameters1/5

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

Schema description coverage is 0% and the description does not mention the sole parameter `issue_number` at all. The agent must rely entirely on the parameter name, with no additional context about how to find or format the issue number.

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?

The description clearly states the tool reads an issue (verb 'Read' + resource 'issue') from the 'synthetic repository', distinguishing it from siblings like get_pull_request and read_file. The action and scope are unambiguous.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives such as get_pull_request or read_file. There are no explicit use cases, exclusions, or comparisons, leaving the agent to infer usage solely from the name and description.

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

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