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Skillsparallel-cli

parallel-cli

Data & analytics

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Updated 10-15 17:27

About this skill

Parallel CLI

One interface for Parallel web data work: extract, deep research, enrichment, findall, memory, and monitor. CLI-backed workflows require parallel-cli installed, authenticated, and funded; the search routing below avoids the CLI where possible.

Routing: MCP first, CLI for depth

  • General web search, quick lookups, fact-checks: use the parallel-search MCP server (web_search) when it is configured. It is free. Do not call parallel-cli search for these. For current official facts (framework/library/API documentation), prefer the harness's native web search per repo convention. When the MCP server is absent, use the harness's native web search, or fall back to parallel-cli search.
  • Escalate to parallel-cli search only when MCP is insufficient: --mode advanced for hard multi-step questions, --after-date freshness, --include-domains / --exclude-domains, --location geo-targeting, or high-volume batch queries.
  • URL content extraction: parallel-cli extract (cleaner than MCP web_fetch for PDFs, JS-heavy pages, and long articles).
  • Deep/exhaustive research (user says "deep", "exhaustive", "comprehensive report", "thorough investigation"): prefer the repository's deep-researcher skill for deep cited research when available (repo convention); research run + poll is the engine and the route when deep-researcher is unavailable.
  • Structured entity lists ("find all X", "list every Y"): findall. Add fields to a list you already have: enrich.
  • Recall prior runs: memory. Continuous change tracking: monitor.
  • Do not use the parallel-task MCP for research or enrichment; the CLI is the tool of record.

Setup

Check and install, requiring parallel-cli >= 0.8.1:

command -v parallel-cli && parallel-cli --version
# install: brew install parallel-web/tap/parallel-cli (macOS)
#          uv tool install "parallel-web-tools[cli]"   (pipx: pipx install "parallel-web-tools[cli]" && pipx ensurepath)
#          npm install -g parallel-web-cli
# upgrade by install method: parallel-cli update | uv tool upgrade "parallel-web-tools[cli]" | pipx upgrade parallel-web-tools | npm update -g parallel-web-cli | brew update && brew upgrade parallel-web/tap/parallel-cli

When the CLI is present but old, detect the install method before upgrading: command -v parallel-cli, then readlink "$(command -v parallel-cli)" if it is a symlink. Paths under ~/.local/share/uv/tools/ mean uv tool install; paths under ~/.local/share/parallel-cli/ mean the standalone installer (use parallel-cli update only for standalone installs).

Authenticate if parallel-cli auth --json shows "authenticated": false or "selected_org_id": "legacy":

parallel-cli login --json   # add --no-browser in headless sessions

This triggers device OAuth. Wait for {"event": "auth_success"}. Then check balance: parallel-cli balance --json get. If zero, ask the user before running parallel-cli balance add <AMOUNT_IN_CENTS>. A 403 on any command usually means balance is required; offer balance --json get and ask before topping up.

Common execution rules

  • Prefer writing results to disk with -o "/tmp/<descriptive>.json" and reading that file over parsing stdout. Large JSON floods or truncates tool output.
  • Do NOT pass --json to poll commands; it floods context. -o saves results to disk.
  • Use --timeout 540 (9 minutes) on polls to stay within tool execution limits.
  • Cite only URLs that appear in command output. Never invent or guess URLs.
  • After any run, tell the user the output file path so they can ask follow-ups.

Workflows

Extract: URL content

parallel-cli extract "https://example.com/article" --json -o "/tmp/<name>.json"

Options: --objective "focus area", -q "keyword" (repeatable), --full-content (complete page body; also retry with this when excerpts come back empty), --no-excerpts, --session-id to group related search/extract calls. Use --full-content when the user asks for a complete page or long-article reproduction; without it the result reflects the excerpt output. On failure (errors field, empty results, 404/timeout), do NOT fabricate content: report the failure, suggest verifying the URL, retrying with --full-content, or locating the current URL via search.

Present the result as Page Title with its URL, followed by the extracted content: preserve every numbered/bulleted item, fact, name, number, date, and quote in the returned content, and reproduce the full page verbatim only when --full-content was requested; strip only obvious noise (nav menus, footers, ads).

Deep research

parallel-cli research run "<topic>" --processor pro-fast --text --no-wait --json
parallel-cli research poll "<RUN_ID>" -o "/tmp/<name>" --timeout 540
parallel-cli research status "<RUN_ID>" --json   # quick status check
  • --text returns a markdown report with inline citations; --text-description steers length/focus. Drop --text for structured JSON.
  • --no-wait is required on run; the call returns instantly with {run_id, interaction_id, result_url, processor, status, output_schema}. Share the result_url for monitoring and the expected latency, and delegate the poll (see Delegation).
  • Default processor pro-fast; follow-ups reuse the prior interaction_id via --previous-interaction-id with a lighter tier (lite-fast). -fast tiers use cached data; non--fast tiers re-fetch fresher data for very recent events. See the reference for the full processor table.
  • Poll writes <name>.json always, plus <name>.md when run used --text. On timeout, re-run the same poll. After completion: share the executive summary printed to stdout, the file paths, and the interaction_id. Do NOT re-share the monitoring URL. Do NOT read the result files into context unless asked.
  • Pass --memory-scope-key to scope research to a workspace.

Enrichment

parallel-cli enrich suggest "Find CEO and recent funding info" --json   # optional: columns + processor recommendation
parallel-cli enrich run --data '[{"company": "Google"}, {"company": "Microsoft"}]' --intent "CEO name and founding year" --target "/tmp/enrichment-<name>.csv" --no-wait --json
parallel-cli enrich poll "<TASKGROUP_ID>" --timeout 540 --output "/tmp/enrichment-<name>.json"
  • CSV source: --source-type csv --source "input.csv" --target "/tmp/enrichment-<name>.csv" --source-columns '[{"name": "company", "description": "Company name"}]'.
  • --target is syntactically required on enrich run even though --no-wait polling writes the real results through poll --output.
  • Use --enriched-columns (array from suggest, in place of --intent) when the user gave a vague intent.
  • Output envelope: {taskgroup_id, url, num_runs}; there is no interaction_id. Tell the user enrichment is running and share the url, then delegate the poll.
  • Output is a JSON array of {input, output} objects regardless of file extension. Report row count, preview a few rows, give the path.

FindAll: entity discovery

parallel-cli findall run "<objective>" -n 50 --no-wait --json   # comprehensive; explicit -n (default 10)
parallel-cli findall poll "<FINDALL_ID>" -o "/tmp/<name>.json" --timeout 540
parallel-cli findall entity-search "<objective>" -t companies -n 100 -o "/tmp/<name>.json"   # fast, throwaway lists only
parallel-cli findall enrich "<FINDALL_ID>" '{"properties":{"ceo":{"type":"string"}}}'         # add fields
parallel-cli findall extend "<FINDALL_ID>" 50                                                 # more matches
parallel-cli findall ingest "<objective>" --json   # preview inferred schema before paying for a run
  • findall run defaults: generator core, match limit 10. For "find all X" / "list every Y" requests, set -n explicitly (5-1000, e.g. -n 50) so the result matches the requested completeness. -g pro for comprehensive coverage, -g base only when the user accepts noise. Exclusions: --exclude '[{"name":"Google","url":"google.com"}]'.
  • entity-search is synchronous, companies/people only, no exclusions/enrichment, and its entity_set_id cannot be used with enrich/extend. Use only when the user explicitly wants a fast, rough list.
  • Filter noise before presenting: drop entries with empty/missing url, names that echo the query, and third-party directory/profile URLs (entity-search's directory links are expected; keep them). Sanity-check -g base matches against source URLs for falsifiable criteria.
  • Present matches as a markdown table, lead with the count, cite each entity's URL.

Memory

parallel-cli memory retrieve --query "serverless inference vendors"   # topic recall
parallel-cli memory retrieve --limit 5                                # recent runs
parallel-cli memory evict --kind task --id "trun_example"
parallel-cli memory clear --confirm-clear
  • Recall prior Task, Monitor, or FindAll runs before launching overlapping work; fetch the source run for full records. Empty results is a successful miss, not an error.
  • On a memory-eligibility error, report the returned reason: it distinguishes rollout, organization settings, account opt-in, and key eligibility. On a key-eligibility error, tell the user to reauthenticate.
  • Fields vary by kind: task uses id/updated_at/input_excerpt/output_excerpt; monitor uses event excerpts; findall uses objective excerpt and matched_count.
  • Evicting/clearing only affects Memory, not the underlying runs. Confirm before clear unless already asked. Ingestion is asynchronous; a just-completed run may not be retrievable yet.

Monitor

parallel-cli monitor create "<query>" --frequency 1d --json        # 1h|1d|1w or daily/weekly; --webhook URL optional
parallel-cli monitor list -n 10 --json
parallel-cli monitor events "<MONITOR_ID>" --json                  # --cursor pages; --event-group-id for full payload
parallel-cli monitor get "<MONITOR_ID>" --json
parallel-cli monitor update "<MONITOR_ID>" --frequency 1w --json
parallel-cli monitor trigger "<MONITOR_ID>" --json                 # one real off-schedule run
parallel-cli monitor cancel "<MONITOR_ID>" --json                  # always confirm; irreversible
  • Monitors are server-side, persist until cancelled, and can deliver events via --webhook. The query cannot be updated; create a new monitor instead.
  • Match frequency to change rate: hourly for prices/news, weekly for filings/staffing.

Delegation

Long-running work (research poll, enrich poll, findall poll) should run in a background subagent with a self-contained prompt: the exact command, the output file path, and the instruction to return only the executive summary and file paths, never inventing URLs. Spawn per harness:

  • opencode: task subagent on opencode-go/deepseek-v4-flash or luna high/max, with Bash access only.

  • Codex: spawn a fresh thread via codex exec (the native multi_agent_v2 tool does not support luna), launched in the background, writing results to a writable path:

    codex exec -C "<repo>" -m gpt-5.6-luna -c model_reasoning_effort="max" --sandbox workspace-write --output-last-message "/tmp/codex-out.md" "<self-contained prompt>" &
# follow-ups: codex exec resume --last "<instruction>"

    The prompt must name the exact parallel-cli ... -o "/tmp/<name>.json" command; the thread needs workspace-write so its -o writes succeed.

  • Claude Code: subagent with pinned model and effort, tools: Bash, bounded maxTurns, dispatched via Task. Prefer a model: inherit-free pin per the repo routing matrix.

  • Kimi Code: Agent tool spawn with subagent_type: coder (or explore for read-only), with a model override where the harness router supports one. UNVERIFIED: luna wiring depends on the local Kimi provider/alias configuration.

Reference

Workflow reference, processor table, JSON envelopes, and version gates: references/parallel-cli-reference.md.