Context

dotagents._context

Assemble effective context (Plan 04).

assemble_context(agent, agents_dir, project_root, global_scope=False)

Assemble the effective context text (markdown) for the given agent.

Returns '' if, after subtracting what the agent's harness already loads, there is nothing new to emit (no empty double of already-loaded content).

Source code in src/dotagents/_context.py

def assemble_context(
    agent: _agents.Agent,
    agents_dir: Path,
    project_root: Path,
    global_scope: bool = False,
) -> str:
    """Assemble the effective context text (markdown) for the given agent.

    Returns '' if, after subtracting what the agent's harness already loads,
    there is nothing new to emit (no empty double of already-loaded content)."""
    filtered_sources = _resolve_and_filter_sources(
        agent, agents_dir, project_root, global_scope
    )
    if not filtered_sources:
        return ""

    assembled_parts = []
    search_roots = [project_root, agents_dir]
    overlay_roots = []

    for level, path, root in filtered_sources:
        try:
            content = path.read_text(encoding="utf-8")
            if root:
                search_roots.append(root)
                if level == "overlay":
                    overlay_roots.append(root)
            assembled_parts.append(f"<!-- Source: {path} -->\n{content.strip()}\n")
        except OSError:
            pass

    text = "\n\n".join(assembled_parts)
    text = _expand_placeholders(text, project_root, overlay_roots)
    text = _inline_referenced_files(text, search_roots)
    text += _get_skills_listing(agents_dir, project_root, global_scope)

    return text

assemble_context_data(agent, agents_dir, project_root, global_scope=False)

Structured form of the assembled context, for --format json.

Shape

{ "agent": , "harness": , "sources": [, ...], # after harness subtraction "context": , "skills": [{"name": ..., "description": ...}, ...], # opt-in listing }

context is the same assembled+inlined text the markdown format emits, but WITHOUT the skills listing appended -- skills are their own structured field so a consumer can render them separately and keep the opt-in distinction.

Source code in src/dotagents/_context.py

def assemble_context_data(
    agent: _agents.Agent,
    agents_dir: Path,
    project_root: Path,
    global_scope: bool = False,
) -> "dict[str, object]":
    """Structured form of the assembled context, for ``--format json``.

    Shape:
        {
          "agent": <registry name>,
          "harness": <harness_id>,
          "sources": [<absolute source path>, ...],  # after harness subtraction
          "context": <assembled markdown text, minus the skills listing>,
          "skills": [{"name": ..., "description": ...}, ...],  # opt-in listing
        }
    ``context`` is the same assembled+inlined text the markdown format emits, but
    WITHOUT the skills listing appended -- skills are their own structured field
    so a consumer can render them separately and keep the opt-in distinction."""
    filtered_sources = _resolve_and_filter_sources(
        agent, agents_dir, project_root, global_scope
    )

    assembled_parts = []
    search_roots = [project_root, agents_dir]
    overlay_roots = []
    source_paths: "list[str]" = []

    for level, path, root in filtered_sources:
        try:
            content = path.read_text(encoding="utf-8")
        except OSError:
            continue
        source_paths.append(str(path))
        if root:
            search_roots.append(root)
            if level == "overlay":
                overlay_roots.append(root)
        assembled_parts.append(f"<!-- Source: {path} -->\n{content.strip()}\n")

    text = "\n\n".join(assembled_parts)
    text = _expand_placeholders(text, project_root, overlay_roots)
    text = _inline_referenced_files(text, search_roots)

    skills = [
        {"name": n, "description": d}
        for n, d in _collect_skills(agents_dir, project_root, global_scope)
    ]

    return {
        "agent": agent.name,
        "harness": agent.harness_id or agent.name,
        "sources": source_paths,
        "context": text,
        "skills": skills,
    }