Interactively creates technical bundles of code, design, and documentation for external review or context sharing. It conducts a brief discovery phase to confirm the targets and format, presents a plan, and then packages multiple project files into a single Markdown file or a portable `.zip` archive.
From context-bundlernpx claudepluginhub richfrem/agent-plugins-skills --plugin context-bundlerThis skill is limited to using the following tools:
acceptance-criteria.mdassets/resources/file-manifest-schema.jsonassets/resources/file-manifest.jsonevals/evals.jsonevals/results.tsvfallback-tree.mdrequirements.inrequirements.txtscripts/bundle.pyscripts/bundle_zip.pyscripts/manifest_manager.pyscripts/path_resolver.pyExecutes pre-written implementation plans: critically reviews, follows bite-sized steps exactly, runs verifications, tracks progress with checkpoints, uses git worktrees, stops on blockers.
Guides idea refinement into designs: explores context, asks questions one-by-one, proposes approaches, presents sections for approval, writes/review specs before coding.
Dispatches parallel agents to independently tackle 2+ tasks like separate test failures or subsystems without shared state or dependencies.
This skill requires Python 3.8+ and standard library only. No external packages needed.
To install this skill's dependencies:
pip-compile ./requirements.in
pip install -r ./requirements.txt
This skill centralizes the knowledge and workflows for creating "Context Bundles." These bundles compile large amounts of code and design context into either a single, portable Markdown file for sharing with other AI agents, or a compressed .zip file for native format sharing and human review.
Because context limits are strict and re-bundling is inefficient, this is a Level 2.0 Interactive Skill. You must follow the phased workflow below to confirm the target files and output format before generating the payload.
Discover, Confirm, and Package. You do not just "list files" or immediately run the bundling scripts. You ensure the bundle is targeted, complete, and annotated, getting user sign-off before execution.
When asked to bundle files, you MUST follow these phases in order. Do not skip to execution.
Evaluate the user's initial request. If it is vague (e.g., "Bundle the auth logic" or "Bundle these files"), ask targeted questions to shape the payload:
ls or codebase search to suggest 3-5 high-value files if they don't know)..md) to paste into an LLM, or a portable Archive (.zip)?Wait for the user's response before proceeding.
Draft the JSON manifest schema conceptually, but DO NOT execute the Python scripts or write to disk yet. Present the proposed plan to the user for approval:
Context Bundle Plan:
- Title: [Proposed Title]
- Format: [.md or .zip]
- Proposed Files/Directories:
1. src/main.py (Core logic)
2. docs/architecture.md (Design reference)
Does this look right? (yes / adjust / exclude certain extensions)
Wait for the user to confirm.
Once confirmed, formulate the actual file-manifest.json on disk.
IMPORTANT: Use directory paths (ending in /) to recursively include entire folders rather than listing 50 files individually.
{
"title": "Bundle Title",
"description": "Short explanation of the bundle's goal.",
"files": [
{
"path": "docs/architecture.md",
"note": "Primary design document."
},
{
"path": "src/module/",
"note": "Implementation logic (recursive)"
}
]
}
Invoke the appropriate script based on the format negotiated in Phase 1.
(Adjust the script path below depending on if you are running this from the plugin root or via an npx installed .agents/ path).
For Markdown (.md):
python3 ./scripts/bundle.py --manifest path/to/file-manifest.json --bundle path/to/output.md
For ZIP Archive (.zip):
python3 ./scripts/bundle_zip.py --manifest path/to/file-manifest.json --bundle path/to/output.zip
Inform the user the payload is ready.