| name | context-provenance |
| description | Build source-grounded context packs with file hashes, line ranges, chunk text, and simple retrieval selection. Use when preparing reliable context for agents, RAG experiments, codebase analysis, or long-document tasks where provenance and source traceability matter.
|
| version | 1.0.0 |
| author | Zijian Guo |
| license | MIT |
| platforms | ["linux","macos"] |
| prerequisites | {"commands":["python3"]} |
| metadata | {"hermes":{"tags":["agent","context-engineering","rag","provenance","citations","memory"]}} |
context-provenance - Source-grounded context packs
Use this skill when an agent needs context that can be traced back to exact
files, line spans, and content hashes.
Research Signal
Long-context models still show position sensitivity, and RAG systems often fail
because retrieved context is stale, weakly attributed, or hard to audit. A small
provenance pack gives agents enough structure to cite and verify sources instead
of relying on copied blobs.
Workflow
- Pack relevant files into chunks with line ranges and hashes.
- Select chunks by query before putting them into the model context.
- Preserve chunk IDs in the final answer or downstream trace.
- Rebuild packs when source files change.
Script
~/.hermes/skills/context-provenance/scripts/context_pack.py
Output Fields
| Field | Meaning |
|---|
id | Stable chunk identifier |
path | Source file path |
start_line, end_line | Inclusive source line range |
sha256 | Hash of the chunk text |
token_estimate | Approximate token count |
text | Chunk content |
Guidance
- Prefer smaller chunks for code and policy text; use larger chunks for prose.
- Keep provenance metadata with any summary derived from a pack.
- Do not mix private corpora unless access control is explicit.
