research-project-orienter

research-project-orienter

Quickly orient an AI assistant inside a research workspace without scanning the whole repository. Reads the .research/ manifest files written by research-context-compressor and produces a single in-conversation orientation memo.

Part of the research-hub skill pack; works alongside Zotero, Obsidian, and NotebookLM workflows but does not require any of them.

This skill is fast and read-only. If .research/ doesn't exist yet, defer to research-context-compressor first.

When to use

Trigger phrases:

• "Understand this research project before helping me."
• "Summarize this repo's research question, data, experiments, and outputs."
• "Build a context map for this paper/project."
• "Orient me in this codebase."
• "What is this repo about?"

Not for:

• Detailed code review — that's a code task.
• Generating new manifests — use research-context-compressor first.
• Literature review — use literature-triage-matrix.

Inputs

Read in this order:

1. .research/project_manifest.yml — top-level orientation. Required.
2. .research/experiment_matrix.yml — experiment status. Read if present.
3. .research/data_dictionary.yml — datasets. Read if present.
4. .research/decisions.md — recent ADRs. Read last 5 if present.
5. .research/open_questions.md — known unknowns. Read all.
6. .research/run_log.md — last 3 entries for context.

Do not read source code, data files, or PDFs unless the manifest points you at a specific path AND the user's question requires it.

What if .research/ doesn't exist?

Tell the user:

This project doesn't have a .research/ manifest yet. I can create one first (loads research-context-compressor skill, takes ~30 seconds and writes 3 small YAML files), or I can fall back to scanning the repo directly (slower, more tokens). Which?

Don't auto-fall-back — ask first. If they pick "scan", read README.md + docs/ + the top-level entrypoint, and produce the memo from that, but caveat: "this orientation came from a one-shot scan; for more reliable future sessions, run research-context-compressor once."

Output: orientation memo

Single message in this exact structure:

## Project orientation: <project_name>

**Research question**: <one sentence from manifest>

**Stage**: <current_stage>  ·  **Last updated**: <last_updated>

**Datasets** (<count>):
- `<id>`: <description>
- ...

**Experiments** (<count>, by status):
- <status>: <id> — <hypothesis (one line)>
- ...

**Main entrypoints**:
- `<path>` — <one-line purpose>
- ...

**Recent decisions** (<count>):
- <date>: <decision title>

**Open questions** (<count>):
- <question text>
- ...

**Evidence artifacts**:
- `<path>` — supports claim/figure
- ...

**Suggested next action**: <based on current_stage>

Length budget: ~200-400 tokens for typical project. Don't pad.

Token-saving behavior

• The whole point of this skill is to save tokens. If you find yourself reading > 5 files outside .research/, stop and tell the user the manifest is incomplete — they should refresh with research-context-compressor.
• Cache-friendly: the orientation memo is identical between sessions if the manifests don't change. Future sessions can paste it back as context.

What NOT to do

• Don't summarize the manuscript — paper-memory-builder does that.
• Don't compare papers — literature-triage-matrix does that.
• Don't propose code changes — that's a separate task.
• Don't invent missing fields. If research_question is empty in the manifest, say "no research question recorded; please add one to .research/project_manifest.yml" rather than guessing.
• Don't read PDFs in data/ or outputs/ unless directly asked.