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baseline_create

Pin a labeled, immutable baseline of an items.json registry, capturing item revisions and artifact-byte fingerprints for verifiable, reproducible rebuilds.

Instructions

Pin a labeled, immutable BASELINE (issue #142, C3) — a {item: revision + content fingerprint} snapshot over an items.json registry (a git-tag / lockfile over the item graph) for reproducible rebuilds. The fingerprint pins the artifact BYTES, so a rebuild is verifiable byte-for-byte.

label: the baseline label (e.g. "v1.0"). registry: path to the items.json sidecar. items: optional subset of item ids to pin (default: every item). base_dir: artifact root for fingerprinting (defaults to the registry's directory). note: optional description. out: optional path — write the git-diffable baseline sidecar there.

Returns the baseline object. Deterministic: same state -> identical bytes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
outNo
noteNo
itemsNo
labelYes
base_dirNo
registryYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it declares immutability, determinism ('same state -> identical bytes'), byte-level fingerprinting, and the optional sidecar write via 'out'. It omits collision/overwrite behavior for an existing label and any permission requirements, which keeps it short of a 5.

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-loads the core action, then lists parameters, then return/determinism. Efficient overall, though the parenthetical jargon ('issue #142, C3', '{item: revision + content fingerprint}') adds density without much selection value.

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 6-param mutation tool with no annotations and no output schema, the description covers parameters, side effects, determinism, and a brief return note ('Returns the baseline object'). It is nearly complete, missing only collision/overwrite and auth context.

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 description coverage is 0%, so the description must compensate and does: all six parameters (label, registry, items, base_dir, note, out) are individually explained with meaning and defaults. This is exactly the value-add the schema lacks.

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 (pin/create) and resource (a labeled, immutable BASELINE snapshot over an items.json registry), with concrete analogies (git-tag/lockfile over the item graph). An agent can distinguish it from baseline_verify or release_package without opening any schema.

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?

The stated purpose ('for reproducible rebuilds', 'verifiable byte-for-byte') implies when it is useful, but there is no explicit when-to-use vs the sibling baseline_verify, no exclusions, and no stated prerequisites. Usage must be inferred from context.

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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