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load_acceptance

Loads a machine-checked AcceptanceSpec from an inline object or JSON path onto a debug session, enabling later run_acceptance evaluation of register, variable, and fault checks.

Instructions

Load a machine-checked AcceptanceSpec (product-spec → deterministic checks) from an inline 'spec' object or a JSON 'path'. Checks: memory_u32 (any memory-mapped register), variable (C global), core_register, no_fault, stopped_at (PC in a symbol). Stored on the session; evaluate with run_acceptance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNoPath to a JSON AcceptanceSpec (alternative to 'spec').
specNoInline AcceptanceSpec {name, description, checks:[...]}.
sessionNoTarget session id (default 'default').

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.15.1

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare the safety profile (readOnly=false, destructive=false, idempotent=false), so the bar is lower. The description adds real context beyond them: state is persisted ('Stored on the session') and the spec's check vocabulary is enumerated, which aids correct authoring. It omits error/failure behavior and permission needs.

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?

Front-loaded with purpose and sources, then the check vocabulary. Dense but every clause earns its place; the check-type enumeration is long yet genuinely informative for authoring a spec.

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?

No output schema, and the safety profile is covered by annotations. The description supplies the source format, the check vocabulary, and the follow-up call, which is sufficient for a loader. Missing only failure/return-format details, which is minor here.

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

Parameters4/5

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

Schema coverage is 100% so the baseline is 3, but the description adds the explicit either/or relationship between the two sources ('inline spec object or a JSON path'), which is meaningful semantics the schema only states separately. No syntax detail for the check schema beyond the type list.

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?

States a specific verb (Load) and resource (AcceptanceSpec), clarifies what the spec represents (product-spec → deterministic checks), enumerates the supported check types, and distinguishes itself from run_acceptance by naming evaluation as the next step. An agent can tell it apart from siblings like import_spec and synthesize_acceptance.

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?

Implies the workflow (load here, then evaluate with run_acceptance), which is useful. However, it never states when to prefer this over near-siblings such as import_spec or synthesize_acceptance, and provides no prerequisites or exclusions.

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