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    status="current",             # Lifecycle status: draft | current | superseded | archived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	Codebase pattern/architecture/testing documents
architect	python-cli-design-spec	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

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="python-cli-design-spec",
)

task-plan

Task plans live exclusively in SAM plan storage. Create them 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.