Workflow: Timetravel Research

Execute a full research workflow using the timetravel adapter library at ~/digital/leviathan/plugins/timetravel/.

Every step spawns a fresh subagent (poly sparkle pattern). State flows only through handoff artifacts at .lev/pm/handoffs/tt-research-*.md.

Trigger

•User wants to research a topic using the timetravel system
•/workflow tt-research "<query>" [--strategy <name>] [--depth quick|standard|deep]

Inputs

Input	Required	Description
`query`	yes	Research query string
`strategy`	no	Override strategy (quick, full, deep, max, academic, social). Default: auto-selected
`depth`	no	Shorthand for strategy: quick=quick, standard=full, deep=deep
`output_dir`	no	Override output directory (default: `~/.config/LEV/research/sessions/<date>/<slug>/`)

Steps

Step 1: Assess Query

Agent Type: Explore Skills: skill://lev-research Research:

•Analyze query complexity: single-fact, comparative, investigative, comprehensive
•Read available strategies: ~/digital/leviathan/plugins/timetravel/src/strategy.ts
•Check user-provided strategy override

Action:

•Classify query type and recommend strategy
•If no strategy specified: quick for single-fact, full for comparative, deep for investigative, max for comprehensive
•Identify relevant adapters and potential gaps
•Create session directory: ~/.config/LEV/research/sessions/<date>/<slug>/

Handoff: .lev/pm/handoffs/tt-research-1-assess.md

yaml

query: <original query>
query_type: single-fact | comparative | investigative | comprehensive
recommended_strategy: <strategy name>
selected_strategy: <final choice>
session_dir: <path>
adapters_needed: [<list>]

Step 2: Health Check

Agent Type: general-purpose Skills: None Research:

•Read handoff from Step 1
•Run cd ~/digital/leviathan/plugins/timetravel && npx timetravel status to check adapter availability

Action:

•Verify all adapters needed by selected strategy are available
•If missing adapters: downgrade strategy or warn user
•Record adapter health snapshot

Handoff: .lev/pm/handoffs/tt-research-2-health.md

yaml

strategy_viable: true | false
available_adapters: [<list>]
missing_adapters: [<list>]
adjusted_strategy: <name if changed, null if same>

Step 3: Execute Search

Agent Type: general-purpose Skills: None Research:

•Read handoffs from Steps 1-2
•Read strategy definition for orchestration mode

Action:

•Run cd ~/digital/leviathan/plugins/timetravel && npx timetravel search "<query>" --strategy <name>
•Capture JSON output
•Save raw results to <session_dir>/artifacts/search_raw.json
•If strategy has synthesizer, verify synthesis was included

Handoff: .lev/pm/handoffs/tt-research-3-execute.md

yaml

strategy_used: <name>
adapters_responded: [<list>]
source_count: <n>
has_synthesis: true | false
raw_results_path: <path>
duration_ms: <n>

Step 4: Synthesize

Agent Type: general-purpose Skills: skill://lev-research Research:

•Read handoff from Step 3
•Read raw results from <session_dir>/artifacts/search_raw.json
•If synthesis already present from oracle, use as base

Action:

•Deduplicate sources across adapters (by URL)
•Rank sources by relevance (title/snippet match to query)
•Generate synthesis: executive summary (2-3 sentences), key findings (3-5), evidence table
•Apply multi-perspective overlay if depth is deep or max
•Save to <session_dir>/synthesis.md

Handoff: .lev/pm/handoffs/tt-research-4-synthesize.md

yaml

unique_sources: <n>
key_findings: <n>
perspectives_applied: [<list or none>]
synthesis_path: <path>
confidence: <0.0-1.0>

Step 5: Generate Report

Agent Type: general-purpose Skills: None Research:

•Read handoffs from Steps 1-4
•Read synthesis from Step 4

Action:

•
Compile final research report using lev-research synthesis template:
- •Executive summary
- •Key findings with source citations
- •Evidence table (claim, source, confidence)
- •Open questions
- •Numbered source list with URLs
•Save to <session_dir>/report.md
•Save <session_dir>/session.json with metadata

Handoff: .lev/pm/handoffs/tt-research-5-report.md

yaml

report_path: <path>
session_json_path: <path>
total_sources: <n>
confidence: <0.0-1.0>

Step 6: Persist Job

Agent Type: general-purpose Skills: None Research:

•Read handoffs from Steps 1-5
•Read job system: ~/digital/leviathan/plugins/timetravel/src/job.ts

Action:

•Create a timetravel job record for re-runs: npx timetravel job create -q "<query>" -s <strategy>
•Record job ID in session metadata
•Optionally schedule if user requested recurring: npx timetravel schedule add <job_id> -c <interval>
•Print final summary with report path and job ID

Handoff: .lev/pm/handoffs/tt-research-6-persist.md

yaml

job_id: <tt-...>
scheduled: true | false
schedule_interval: <cron or null>
report_path: <path>
status: complete

Outputs

•Research report: <session_dir>/report.md
•Synthesis: <session_dir>/synthesis.md
•Raw results: <session_dir>/artifacts/search_raw.json
•Session metadata: <session_dir>/session.json
•Job record: ~/.config/LEV/timetravel/jobs/<job_id>/
•6 handoff artifacts in .lev/pm/handoffs/tt-research-*.md

Validation

• Search returned at least 1 source
• Synthesis includes executive summary and key findings
• Report follows lev-research template structure
• Session directory contains all expected files
• Job record created and retrievable via timetravel job list
• All 6 handoff files created

Usage

bash

/workflow tt-research "state of AI agent frameworks 2026"
/workflow tt-research "rust vs go for CLI tools" --strategy academic
/workflow tt-research "trending AI on twitter" --strategy social
/workflow tt-research "comprehensive LLM evaluation" --depth deep

Technique Map

•Role definition - Clarifies operating scope and prevents ambiguous execution.
•Context enrichment - Captures required inputs before actions.
•Output structuring - Standardizes deliverables for consistent reuse.
•Step-by-step workflow - Reduces errors by making execution order explicit.
•Edge-case handling - Documents safe fallbacks when assumptions fail.

Technique Notes

These techniques improve reliability by making intent, inputs, outputs, and fallback paths explicit. Keep this section concise and additive so existing domain guidance remains primary.

Prompt Architect Overlay

Role Definition

You are the prompt-architect-enhanced specialist for workflow-tt-research, responsible for deterministic execution of this skill's guidance while preserving existing workflow and constraints.

Input Contract

•Required: clear user intent and relevant context for this skill.
•Preferred: repository/project constraints, existing artifacts, and success criteria.
•If context is missing, ask focused questions before proceeding.

Output Contract

•Provide structured, actionable outputs aligned to this skill's existing format.
•Include assumptions and next steps when appropriate.
•Preserve compatibility with existing sections and related skills.

Edge Cases & Fallbacks

•If prerequisites are missing, provide a minimal safe path and request missing inputs.
•If scope is ambiguous, narrow to the highest-confidence sub-task.
•If a requested action conflicts with existing constraints, explain and offer compliant alternatives.