Create Artifact Skill | Agent Skills

Create Artifact

Register your deliverable through the configured content provider with mcp__plugin_dh_backlog__artifact_register, or use the artifact register CLI subcommand in scripting contexts. Pass the content in the registration call and return only its logical ID.

Storage boundary

artifact_register writes through the selected provider; agents do not choose or access its storage layer.
artifact_read(item_id, artifact_type) retrieves the current artifact through the same boundary.
Background agents return the logical ID instead of repeating the document in their completion message.

Invocation

MCP:

mcp__plugin_dh_backlog__artifact_register(
    item_id=<int | str>,          # Backlog item identifier — REQUIRED
    artifact_type=<str>,          # Artifact type string — REQUIRED (see table below)
    artifact_id=<str>,            # Logical identifier — REQUIRED
    status="current",             # Lifecycle status: draft | current | superseded | archived
    agent=<str>,                  # Name of the producing agent (default: "")
    content=<str>,                # Non-empty full artifact content — REQUIRED
)

CLI equivalent (scripting/dispatch contexts):

uv run "${CLAUDE_PLUGIN_ROOT}/sam_schema/cli.py" artifact register \
  --item-id <identifier> \
  --artifact-type <str> \
  --artifact-id <str> \
  --status "current" \
  --agent <str> \
  --content <str>

--status and --agent are optional (same defaults as the MCP form). The examples below use the MCP form; substitute the same values into the CLI flags above for a scripting context.

Return value: dict with keys registered (bool), artifact_count (int), action ("added" or "updated"), content_stored (bool), messages, warnings. Check action in your STATUS: DONE report — do NOT paste the full content.

Parameters

`artifact_type`

One of the recognized type strings:

| artifact_type | Producing agent | When to use | |---|---|---| | feature-context | feature-researcher | Discovery document: WHO/WHAT/WHEN/WHY analysis | | codebase-analysis | codebase-analyzer, code-review-architecture | Codebase pattern/architecture/testing documents and dependency graphs; several per item | | code-review | code-reviewer | Code review verdict; one per reviewed task, read by the quality gate via artifact_id | | architect | {resolved_agent} (language-plugin design-spec agent, resolved via profile_list) | Architecture spec with interfaces and contracts | | T0-baseline | t0-baseline-capture | Pre-implementation baseline of acceptance criteria | | TN-verification | tn-verification-gate | Post-implementation verification results | | research | any research agent | Investigation findings, coverage analysis, rationale | | task-plan | sam_plan (internal, auto-registered) | Never call artifact_register directly for this type — see task-plan below | | dispatch-plan | dispatch_create_plan (internal, auto-registered) | Milestone dispatch plan; created automatically by the dispatch_create_plan MCP tool, not by direct registration | | audit-report | doc-drift-auditor | Documentation drift audit findings for a completed work item |

`artifact_id`

Use a stable logical identifier, such as feature-context-{slug}, architect-{slug}, codebase-patterns-{slug}, T0-baseline-{slug}, or TN-verification-{slug}. Consumers use the owner and artifact type to discover content; the identifier distinguishes multiple artifacts of the same type.

`content`

Pass a non-empty full markdown string. The current registration contract requires content=; without it, the call is invalid and artifact_read(item_id, artifact_type) cannot return the document.

Examples by artifact type

feature-context

mcp__plugin_dh_backlog__artifact_register(
    item_id=1770,
    artifact_type="feature-context",
    artifact_id="feature-context-my-feature",
    content=feature_context_markdown,
    agent="feature-researcher",
)

codebase-analysis (one call per focus area)

mcp__plugin_dh_backlog__artifact_register(
    item_id=1770,
    artifact_type="codebase-analysis",
    artifact_id="codebase-patterns-my-feature",
    content=patterns_markdown,
    agent="codebase-analyzer",
)

mcp__plugin_dh_backlog__artifact_register(
    item_id=1770,
    artifact_type="codebase-analysis",
    artifact_id="codebase-architecture-my-feature",
    content=architecture_markdown,
    agent="codebase-analyzer",
)

architect

mcp__plugin_dh_backlog__artifact_register(
    item_id=1770,
    artifact_type="architect",
    artifact_id="architect-my-feature",
    content=architect_markdown,
    agent="{resolved_agent}",
)

task-plan

task-plan is a valid artifact_register type, but it is written internally — sam_plan(config={"action": "create", "issue": N, ...}) auto-registers it, making the plan readable via artifact_read/artifact_list for worktree-isolated agents. Never register this type directly through artifact_register; create plans with mcp__plugin_dh_sam__sam_plan(config={"action": "create", ...}) and retrieve them with mcp__plugin_dh_sam__sam_plan(plan="{plan_ref}", config={"action": "read"}).

research (secondary documents, rationale, coverage analysis)

mcp__plugin_dh_backlog__artifact_register(
    item_id=1770,
    artifact_type="research",
    artifact_id="swarm-rationale-my-feature",
    content=rationale_markdown,
    agent="swarm-task-planner",
)

STATUS: DONE report format

Do NOT paste the full document content. Report only:

STATUS: DONE
ARTIFACT: type={artifact_type}, action={action}, content_stored={content_stored}, chars={len(content)}

Include a <concerns> block if quality issues were found during the work.

Agent Skills: Create Artifact

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