SKILL.md
$2b
Optional with --text: pass --text-description "Keep under 1500 words, focus on M&A activity" to steer length, format, or focus.
If this is a follow-up to a previous research or enrichment task where you know the interaction_id, add context chaining:
parallel-cli research run "$ARGUMENTS" --processor lite-fast --text --no-wait --json --previous-interaction-id "$INTERACTION_ID"By chaining interaction_id values across requests, each follow-up question automatically has the full context of prior turns — so you can drill deeper without restating what was already researched. Use a lighter processor (lite-fast or base-fast) for follow-ups since the heavy lifting was done in the initial turn.
This returns instantly. Do NOT omit --no-wait — without it the command blocks for minutes and will time out.
Processor options (choose based on user request):
Processor
Expected latency
Use when
lite-fast
10–60s
Quick lookups, follow-ups
base-fast
15–100s
Simple questions
core-fast
1–5 min
Moderate research
pro-fast
2–10 min
Default — exploratory research, good depth/speed balance
ultra-fast
5–25 min
Multi-source deep research (~2× cost)
ultra2x-fast / ultra4x-fast / ultra8x-fast
up to 2 hr
Hardest questions, only when explicitly requested
Notes on the -fast suffix: -fast tiers use cached web data and are quicker. The non-fast variants (pro, ultra, etc.) re-fetch fresher data — slower but better for very recent events. Default to -fast unless the user specifically asks about news from the last day or two.
Run parallel-cli research processors to see the full list with latencies.
Parse the JSON output to extract the run_id, interaction_id, and monitoring URL. Immediately tell the user:
- Deep research has been kicked off
- The expected latency for the processor tier chosen (from the table above)
- The monitoring URL where they can track progress
Tell them they can background the polling step to continue working while it runs.
Step 2: Poll for results
parallel-cli research poll "$RUN_ID" -o "$FILENAME" --timeout 540Important:
- Use
--timeout 540(9 minutes) to stay within tool execution limits
- Do NOT pass
--json— the full output is large and will flood context. The-oflag writes results to files instead.
- With
-o "$FILENAME":
$FILENAME.jsonis always written (metadata + basis)
$FILENAME.mdis written **only if step 1 used--text** (markdown report)
- The poll command prints an executive summary to stdout when the research completes. Share this executive summary with the user — it gives them a quick overview without having to open the files.
- Pass
--forceif re-polling and you want to overwrite existing files
If the poll times out
Higher processor tiers can take longer than 9 minutes. If the poll exits without completing:
- Tell the user the research is still running server-side
- Re-run the same
parallel-cli research pollcommand to continue waiting
Response format
After step 1: Share the monitoring URL (for tracking progress only — it is not the final report).
After step 2:
- Share the executive summary that the poll command printed to stdout
- Tell the user the generated file paths:
$FILENAME.md— formatted markdown report (if--textwas used)
$FILENAME.json— metadata and basis
- Share the
interaction_idand tell the user they can ask follow-up questions that build on this research (e.g., "drill deeper into X" or "compare that to Y")
Do NOT re-share the monitoring URL after completion — the results are in the files, not at that link.
Ask the user if they would like to read through the files for more detail. Do NOT read the file contents into context unless the user asks.
**Remember the interaction_id** — if the user asks a follow-up question that relates to this research, use it as --previous-interaction-id in the next research or enrichment command.
Setup
Requires parallel-cli (installed and authenticated). If parallel-cli --version fails, or if a later command fails with an authentication error, tell the user to see https://docs.parallel.ai/integrations/cli and stop.