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Mipiti
by Mipiti

Get Assertion Types

get_assertion_types

Retrieve the complete catalogue of assertion types accepted by submit_assertions, including required and optional parameters, soundness classes, and worked examples, so you can write valid assertions before submitting them.

Instructions

List the assertion types submit_assertions accepts, with their params.

Read-only. Returns the catalogue as structured data: every type, what it proves, its soundness class, which params it requires, which it accepts (an array-valued param carries its item_schema), and a worked example. soundness_classes defines the five classes by the fact a pass establishes, weakest to strongest — presence, under_approximating_scan, existential_witness, sound_over_approximation, by_construction — and sound_classes names the two that can credit a for-all clause. covers gives the accepted form of a binding declaration.

Call this before writing assertions. submit_assertions names the types and their required params in its own description, but descriptions are prose a client may present only in part, and a half-list reads exactly like a whole one. This returns data, so what you get back is the complete contract.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typesNoOptional comma-separated type names to return (e.g. "file_exists,pattern_absent"). Omit for all of them.
server_versionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.71.1

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden. It states "Read-only" and describes the return payload in detail: every type, what it proves, its soundness class, required/optional params, item_schema for array params, a worked example, and the semantics of soundness_classes, sound_classes, and covers. This goes well beyond a generic list call and gives the agent a clear expectation of behavior and output structure, even without an output schema reference.

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 longer than typical, but every sentence contributes meaningful detail: purpose, output semantics, and usage rationale. It is front-loaded with the core purpose and then expands. While slightly verbose, it avoids redundancy and earns its length through dense, relevant content.

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?

The tool has an output schema, so return-value details could be omitted, but the description still explains the output's semantic structure, which is valuable. The main gap is the unexplained server_version parameter, but the tool itself is simple and well-contextualized. Overall, the description is sufficient for correct invocation, with only that minor parameter gap.

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

Parameters2/5

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

The input schema has only 50% coverage, with server_version lacking any description. The tool description does not mention either of the tool's own parameters (types, server_version), so it adds no semantic value beyond the schema. Since the description is expected to compensate for schema gaps, the failure to explain server_version is a significant omission, leaving the agent without guidance on a required parameter.

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 opens with a precise statement of purpose: "List the assertion types submit_assertions accepts, with their params." It clearly specifies the resource (assertion types) and the action (list), and immediately connects to the sibling tool submit_assertions, distinguishing itself as the authoritative catalogue. This is unambiguous and fully differentiates the tool from its siblings.

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

Usage Guidelines5/5

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

The description gives explicit guidance: "Call this before writing assertions." It explains why this tool is preferred over relying on submit_assertions' prose description, noting that prose may be partially presented and a half-list reads like a whole one. This provides a clear when-to-use directive and justifies why the structured data is superior, covering the alternative explicitly.

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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