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falsepass

falsepass

by Super-Eric
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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falsepass_scan

Statically pre-scan reward source code in a .py file or folder without installing or running anything, returning pattern hints that flag potential false passes for audit confirmation.

Instructions

Static pre-scan of reward source code (a .py file or a folder). Nothing is installed or run. Returns hints: patterns worth a look, each to be confirmed by an audit.

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": {
      "path": "<path>"
    },
    "name": "falsepass_scan"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYesa .py file or a folder of reward code, relative to workdir
workdirNothe folder whose audits/ holds the audits (default: the current directory).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.15.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations supplied, the description carries the full behavioral burden and does well by disclosing that 'Nothing is installed or run' and that results are 'hints' rather than definitive findings. It does not cover error conditions or permission requirements, but for a static scanner it provides the most important safety and output semantics.

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

Conciseness5/5

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

Two sentences with no wasted wording. The static nature, no-execution guarantee, and hint-based output are front-loaded in a logical order.

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?

For a simple two-parameter static scanner with full schema descriptions and no output schema, the description covers what the tool does, what it does not do, and what kind of results it returns. Minor gaps around explicit usage selection remain, but nothing essential is missing.

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?

Schema coverage is 100%, so the input schema already documents both parameters thoroughly. The description adds the useful context that the path is reward source code and can be a .py file or folder, but it does not add meaning beyond the schema for the workdir parameter. 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?

The description gives a specific verb and resource: 'Static pre-scan of reward source code (a .py file or a folder).' It also distinguishes this from a full audit by saying each hint is 'to be confirmed by an audit,' so an agent can tell this is preliminary scanning rather than the audit itself.

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

Usage Guidelines3/5

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

The word 'pre-scan' and the phrase 'confirmed by an audit' imply this should be used before running an audit, but the description never explicitly states when to choose this tool over alternatives or when not to use it. The usage is clear by implication rather than by direct guidance.

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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