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Generate a stochastic variant pack from a seed look

variant_pack

Creates a pack of parameter variants by perturbing an anchor look within slider ranges, writing a morph_pack-compatible JSON to the Obsidian vault for direct unpacking.

Instructions

Generate N perturbed variants around an anchor parameter look and write the whole pack to the Obsidian vault as a morph_pack-compatible JSON. Probes the target COMP's customPars for slider ranges to clamp + integer-round per param, then perturbs each variant uniformly within ±delta_range × (normMax − normMin). The resulting file is consumed directly by morph_pack (action=unpack). Requires TDMCP_VAULT_PATH.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesPack name. File defaults to MorphPacks/<name>.morphpack.json.
seedNoRNG seed for repeatable packs.
countNoNumber of perturbed variants (1..64).
parentNoParent COMP recorded into provenance.container_path./project1
comp_pathNoCOMP whose customPars give slider ranges for clamping. Defaults to target_path else parent.
overwriteNoAllow replacing an existing pack file.
seed_lookYesAnchor look: { paramName: number }. Names must be numeric custom pars on comp_path.
vault_pathNoOverride default MorphPacks/<name>.morphpack.json. Resolved via Vault.resolve.
delta_rangeNoPerturbation magnitude as fraction of each param's slider span.
target_pathNoRecorded into provenance.target_path so morph_pack can unpack standalone.
include_seedNoIf true, slot v00 is the seed look itself.
interpolationNoRecorded into provenance.linear
variant_prefixNoSlot id prefix.
Behavior4/5

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

Annotations indicate readOnly=false and destructive=false; description adds that it writes to the vault, requires TDMCP_VAULT_PATH, and details the clamping/rounding/perturbation algorithm. This goes beyond the annotation flags by disclosing input probing and file output behavior, though it doesn't discuss failure modes or overwrite 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?

Three sentences, each serving a purpose: purpose, algorithm, and integration with morph_pack. No redundant phrasing; front-loaded with the core action.

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 complex tool with 13 parameters and no output schema, the description covers the key aspects: what it generates, where it writes, the environment requirement, and downstream consumer. Minor omission is return value details, but the file-based output is adequately implied.

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 descriptions provide baseline. The description adds value by explaining how delta_range scales with slider span and how comp_path is used to read customPars, which clarifies parameter semantics beyond the schema. It doesn't enumerate each parameter but contextualizes the algorithm.

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?

Description clearly states the tool generates N perturbed variants around an anchor look and writes a morph_pack-compatible JSON to the Obsidian vault. It identifies the specific resources (anchor parameter look, COMP customPars, vault) and distinguishes itself from morph_pack by being the generation step.

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

Usage Guidelines4/5

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

Description explains the workflow (probes customPars, perturbs, writes for morph_pack unpack), implying when to use it. However, it does not explicitly exclude alternatives like create_preset_morph or state when not to use it, so it gets a 4.

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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