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Provenance Stamp

provenance_stamp

Generate a .provenance.json sidecar for any artifact, recording sha256 checksum, file size, git metadata, author, tags, and notes to enable offline provenance tracking.

Instructions

Writes a .provenance.json sidecar next to a saved artifact (tox, recipe note, recipe bundle, component bundle). Records the sha256 checksum, file size, mtime, source COMP path, originating tdmcp tool, toolchain versions, best-effort git metadata, author, tags, and freeform notes. Offline — no TD bridge required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
artifact_pathYesAbsolute or vault-resolved path to the file to stamp.
artifact_kindNoWhat kind of artifact this is — hint only, not validated.other
sourceNoWhere/what produced this artifact.
authorNoAuthor label. Defaults to TDMCP_AUTHOR env var then os.userInfo().username.
tagsNoFree-form tags for vault search.
notesNoShort human note to attach to the sidecar.
extraNoTool-specific extras, e.g. {nodes:7, connections:9}.
overwriteNoReplace an existing sidecar. Set false to refuse if one exists.
include_gitNoCapture git commit/branch/dirty from the artifact's directory (best-effort).
Behavior3/5

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

With no annotations provided, the description carries full burden. It states the tool writes a sidecar, records specific fields, and operates offline, but does not disclose error handling, side effects (e.g., overwrite behavior), or what happens if the artifact is missing. The description is partially transparent but missing key behavioral details.

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 two sentences, front-loaded with the core action, followed by a list of recorded content and offline capability. No redundant words, every sentence adds value. Excellent conciseness.

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

Completeness2/5

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

Given 9 parameters, no output schema, and no annotations, the description is too brief. It omits mention of key parameters like artifact_kind, author, tags, overwrite, and include_git, which are critical for controlling the tool's behavior. The description leaves the agent under-informed about important options.

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 description coverage is 100%, baseline 3. The description adds value beyond schema by listing the recorded fields (sha256, file size, etc.), which clarifies what parameters like 'source' and 'extra' contribute to the output. This extra context helps the agent understand the tool's purpose, earning a higher score.

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 the tool's purpose: 'Writes a .provenance.json sidecar next to a saved artifact'. It specifies the verb (writes) and the resource (sidecar file), and lists the contents recorded. The tool is distinct from siblings, as none other perform this specific stamping action.

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 description mentions 'Offline — no TD bridge required', which gives context, but does not explicitly state when to use this tool versus alternatives or when not to use it. It lacks guidance on prerequisites or workflows, leaving the agent to infer usage.

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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