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falsepass

falsepass

by Super-Eric
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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falsepass_completion

Retrieves the full text of a specific audit completion by env and completion_id when the results digest shows only its start and end.

Instructions

The full text of one completion from the last run (a completion_id from the results): the digest shows only its start and end.

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": {
      "env": "<env>",
      "completion_id": "<completion_id>"
    },
    "name": "falsepass_completion"
  }
}

Input Schema

NameRequiredDescriptionDefault
envYesthe audit's name as falsepass_init returned it: the folder under workdir/audits/
workdirNothe folder whose audits/ holds the audits (default: the current directory).
completion_idYesa completion_id from the results digest

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.15.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It does disclose useful behavior — that results are limited to 'the last run' and that output is untruncated full text versus the digest's start/end excerpt — but says nothing about error behavior for an unknown completion_id, permissions, or response shape.

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?

One sentence, front-loaded with what is returned, followed by the contrast with the digest. Nothing is wasted and the key qualifier ('from the last run') appears early.

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 read-only single-item retrieval with three fully documented parameters and no output schema, the description covers what the tool returns and where the ID comes from. Only minor gaps remain, such as failure modes for an invalid or expired completion_id.

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 baseline is 3. The description reinforces that completion_id originates from the results digest, matching the schema text, but adds no new semantics such as format, case sensitivity, or what happens with a stale ID.

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

Purpose4/5

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

The description names a specific resource — the full text of a single completion — and scopes it to 'the last run', which lets an agent tell it apart from the results digest it references. The retrieval verb is implied by 'The full text of' rather than stated, but the purpose is unambiguous.

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?

It gives an implicit selection rule: use this when the digest, which 'shows only its start and end', is insufficient. However, no sibling tool is named as the alternative and there is no explicit when-not-to-use guidance, so the agent must infer the routing from the parenthetical.

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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