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liangjunglj-cpu

Almond MCP

list_capsules

Discover Grasshopper capsules with typed, audited contracts to find which are executable via run_gh_definition.

Instructions

Lists Grasshopper capsules: GH definitions with a typed, audited input/output contract that can be executed via run_gh_definition.

Call this FIRST to discover what capsules exist before calling run_gh_definition. Each entry is a compact card with capsule_id, capability, structure_type, audited flag, and the reserved ALMOND_IN_* / ALMOND_OUT_* port names. Only capsules with audited=true can actually run; audited=false capsules are retrieval context only (read them via get_logic_by_id instead).

Args: capability: Optional filter: "analyze", "generate", "form_find", or "aggregate". audited_only: When true, list only capsules that run_gh_definition will accept. Returns: JSON with total and a list of compact capsule cards.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
capabilityNo
audited_onlyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description fully discloses that only audited=true capsules can run, audited=false are retrieval context only, and lists output fields. It lacks details on pagination or error handling, but given the output schema likely covers structure, this is adequate.

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?

The description is well-structured with purpose, usage note, parameter explanation, and return format. Every sentence adds essential information; no fluff or repetition.

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

Completeness5/5

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

Given the complexity of capsules and the presence of an output schema, the description adequately covers the tool's role, parameters, behavioral constraints, and return fields. It enables correct selection and invocation.

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

Parameters5/5

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

Schema coverage is 0%, so the description entirely explains both parameters: capability (an optional filter with enumerated values provided) and audited_only (a boolean to filter runnable capsules). Adds value beyond the schema.

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 that the tool lists Grasshopper capsules, which are GH definitions with typed contracts executable via run_gh_definition. It distinguishes itself from siblings like run_gh_definition and get_logic_by_id, leaving no ambiguity about its function.

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?

Explicitly instructs 'Call this FIRST to discover what capsules exist before calling run_gh_definition.' It also clarifies when to use get_logic_by_id for non-audited capsules, providing clear conditional 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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