| name | creating-handoffs |
| description | Use when work context must transfer to another session or person. Triggers: create a handoff, hand off this work, summarize context for the next session, prepare a handoff. |
Creating Handoffs
Produce a handoff document that transfers full working context to the next session with no information loss.
Interaction mode
This skill leans Direct by default. For the full Collaborative-vs-Direct protocol and override rules, see the Interaction Modes reference in the ai-research-workflows:using-research-workflows skill.
Process
1. Gather context
Run these in parallel where possible:
Git state:
- Current branch name
- Current commit hash (short)
- Summary of uncommitted changes (
git status and git diff --stat)
Workflow artifacts — search docs/rse/specs/ (then legacy .agents/) for:
research-*.md — research documents
plan-*.md — plan documents
experiment-*.md — experiment documents
implement-*.md — implementation documents
validation-*.md — validation reports
handoff-*.md — previous handoff documents
Session context:
- Review the conversation to understand what tasks were worked on.
- Identify the current workflow phase (Research, Plan, Iterate Plan, Experiment, Implement, Validate).
- Note which workflow artifacts were produced or referenced this session.
Research state (for research/scientific work):
- Random seeds, the active environment/lockfile (
pixi.lock / uv.lock), and
dataset versions/paths/checksums in play.
- Partial or intermediate results, saved checkpoints/outputs, and any
long-running experiment or job still in flight — with how to check or resume it.
2. Determine what's relevant
From the gathered context, identify:
- Tasks: What was being worked on and the status of each (completed, in progress, planned).
- Current phase: Where in the workflow cycle the work sits.
- Artifacts: Which
docs/rse/specs/ documents are relevant.
- Critical files: The 2–3 most important files the next session must read first.
- Recent changes: What code was modified (use
file:line references).
- Learnings: Important discoveries, patterns, or gotchas.
- Research state: seeds, environment/lockfile, data versions, and partial
results needed to resume (see
ai-research-workflows:ensuring-reproducibility).
- Verification status: what is tested and passing vs. broken or unverified,
and what is uncommitted or unpushed.
- Next steps: What the next session should do, in priority order.
Report true state — don't paper over broken work
A handoff must reflect reality, not a tidy fiction. Before generating the
document, explicitly surface:
- Uncommitted / unpushed work — name it; the next session cannot see your
working tree.
- Failing or unrun tests — state which, with the actual status; never imply
green when it isn't.
- Unreproducible or unverified results — flag any result that has not been
reproduced or whose provenance is incomplete.
Put these in a "Known-broken / unverified" callout in the handoff. A clean-looking
handoff that hides broken state is worse than none — it sends the next session
down a false trail.
3. Generate the handoff document
Filename format: handoff-YYYY-MM-DD-HH-MM-<slug>.md
YYYY-MM-DD-HH-MM is the current date and time.
<slug> is a brief kebab-case description of the work.
- Example:
handoff-2025-06-15-14-30-auth-system-refactor.md
Read the handoff template:
assets/handoff-template.md
Fill out all sections:
- Replace all placeholder text with actual content.
- Remove artifact sections that don't apply (e.g., if no experiments were run, remove Experiment Reports).
- Be specific — use
file:line references, not vague descriptions.
- Name the recommended next skill for the receiving session based on the current phase (e.g.,
ai-research-workflows:implementing-plans, ai-research-workflows:validating-implementations).
Save to docs/rse/specs/handoff-YYYY-MM-DD-HH-MM-<slug>.md.
4. Present the handoff
After saving, present a concise summary:
## Handoff Created
**File:** `docs/rse/specs/handoff-<filename>.md`
**Current Phase:** [phase]
**Status:** [brief status of work]
### Quick Summary
[2–3 sentence summary of what was done and what's next]
### For the Next Session
Start by running:
> Read the handoff document at `docs/rse/specs/handoff-<filename>.md` and resume the work described within.
Or to continue with the workflow:
> [recommended-skill] [relevant arguments]
Writing guidelines
- More information, not less. The template is the minimum; always include more when necessary.
- Be thorough and precise. Include both top-level objectives and lower-level details.
- Avoid excessive code snippets. Prefer
path/to/file.ext:line references. Only include code blocks when describing an error being debugged or a critical pattern.
- Cross-reference workflow artifacts. Link to research, plan, experiment, and implementation documents by filename so the next session can read them.
- Name the recommended next skill. Based on where you are in the workflow, tell the next session which skill to invoke next (e.g.,
ai-research-workflows:implementing-plans, ai-research-workflows:validating-implementations).
- Include learnings. Capture non-obvious insights about the codebase, patterns that matter, or gotchas encountered.
Common Mistakes
- Dumping raw history instead of a focused summary — pasting the full conversation or every git commit message produces an unreadable wall of text. Distil to what the next session actually needs to act.
- Omitting the critical files to read first — the most common cause of a slow hand-off restart is not knowing where to begin. Always name the 2–3 files the next session must read before doing anything else.
- Not naming the recommended next skill — leaving "next steps" vague forces the receiving session to re-derive the workflow position. Always state the exact skill to invoke next (e.g.,
ai-research-workflows:implementing-plans).
- Missing learnings and gotchas — documenting what was done without capturing why certain decisions were made, or what dead ends were hit, forces the next session to rediscover them.
- A clean-looking handoff that hides broken state — omitting failing tests, uncommitted work, or unverified results sends the next session down a false trail; surface them in a "Known-broken / unverified" callout.
- Omitting research state — leaving out seeds, environment/lockfile, dataset versions, partial results, or in-flight jobs makes the work impossible to resume or reproduce; capture them for any research/scientific work.
Cross-references
- Use
ai-research-workflows:implementing-plans as the recommended next skill when a plan is approved and ready to execute.
- Use
ai-research-workflows:validating-implementations when implementation is complete and needs verification.
- Use
ai-research-workflows:planning-implementations or ai-research-workflows:iterating-plans when the next session needs to (re-)design the approach.
- All handoff documents are picked up automatically by
ai-research-workflows:using-research-workflows when it surveys docs/rse/specs/ (and legacy .agents/).