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normallygaussian

Parallel FindAll

by NormallyGaussian · GitHub ↗ · v1.0.3 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install parallel-findall
Description
Discover entities (companies, people, products) matching a natural-language description via the Parallel FindAll API. Use when the user wants to 'find all X'...
README (SKILL.md)

Parallel FindAll

Discover entities matching a natural-language description. FindAll is for "give me a list of things that match this criteria" tasks — companies, people, products, papers, anything enumerable. Returns structured entities, not webpages or prose.

When to Use

Trigger this skill when the user asks for:

  • "find all [X]", "list every [Y] that…"
  • "discover [companies / people / products] matching…"
  • "give me a list of [SaaS in vertical Z / YC W24 dev tools / Series A AI startups]"
  • Bulk entity discovery where the answer is a structured list, not a narrative

Use Search for "what is X?"; use FindAll for "list every X that matches Y".

Quick Start

parallel-cli findall run "AI startups that raised Series A in 2026" --json

CLI Reference

Basic Usage

parallel-cli findall run "\x3Cobjective>" [options]
parallel-cli findall status frun_xxx --json
parallel-cli findall poll frun_xxx --json
parallel-cli findall result frun_xxx --json
parallel-cli findall extend frun_xxx \x3Cn> --json
parallel-cli findall cancel frun_xxx

Common Flags

Flag Description
-g, --generator Generator tier: preview, base, core (default), pro
-n, --match-limit Max matched candidates, 5-1000 (default: 10)
--exclude '\x3Cjson>' Entities to exclude (JSON array of {name, url})
--no-wait Return immediately with frun_xxx; poll separately
--dry-run Preview the schema FindAll will use, without creating a run
--json Output as JSON
-o, --output \x3Cfile> Save full result to file

Examples

Basic discovery:

parallel-cli findall run "Find roofing companies in Charlotte NC" --json

Larger result set with core generator:

parallel-cli findall run "AI startups that raised Series A in 2026" -n 50 --json

pro tier for deeper coverage:

parallel-cli findall run "YC W24 dev tools companies" -g pro -n 100 --json

Preview the schema before running:

parallel-cli findall run "Find Series B fintechs in Latin America" --dry-run --json

Exclude already-known entities:

parallel-cli findall run "Find AI startups in healthcare" \
  --exclude '[{"name": "Hippocratic AI", "url": "hippocraticai.com"}]' \
  --json

Async — launch then poll separately:

parallel-cli findall run "AI startups that raised Series A in 2026" --no-wait --json
# returns frun_xxx
parallel-cli findall status frun_xxx --json
parallel-cli findall poll frun_xxx --json    # waits and returns result

Extend an existing run with more matches:

parallel-cli findall extend frun_xxx 50 --json

Cancel a running job:

parallel-cli findall cancel frun_xxx

Best-Practice Prompting

Objective

1-3 sentences describing:

  • The entity type (companies / people / products / papers / etc.)
  • The matching criteria (vertical, geography, time range, status)
  • Any quality filters ("active", "publicly listed", "open-source")

Generator Tier

  • preview — fast scan, low coverage. Useful only for quick sanity checks.
  • base — broad and fast, but noisy (query echoes, no-URL entries, category placeholders). Use only when the user explicitly accepts noise.
  • core (default) — best balance of coverage and quality.
  • pro — deeper coverage, slower. Use for high-stakes discovery where missing matches is costly.

Match Limit

Pick the smallest -n that satisfies the user's intent. Default 10 is fine for "show me a few"; bump to 50–100 for "list every X". Max 1000.

Response Format

findall run returns JSON with:

  • findall_idfrun_xxx
  • statusrunning / completed / cancelled / failed
  • schema — the JSON Schema FindAll built for the matches
  • matches[] — array of entities, each with fields per the schema (typically name, url, plus skill-specific extracted fields)

Output Handling

When relaying matches to the user:

  • Filter noise: drop entries with empty url, query-echo names, or category placeholders. Especially important on -g base.
  • Group by source domain if the result set is large — helps the user spot duplicate sources.
  • Echo findall_id so the user can extend or cancel later.

Running Out of Context?

For large result sets (-n ≥ 50), save and use sessions_spawn:

parallel-cli findall run "\x3Cobjective>" -n 100 --json -o /tmp/findall-\x3Ctopic>.json

Then spawn a sub-agent:

{
  "tool": "sessions_spawn",
  "task": "Read /tmp/findall-\x3Ctopic>.json and produce a deduplicated table grouped by category.",
  "label": "findall-summary"
}

Error Handling

Exit Code Meaning
0 Success
1 Unexpected error (network, parse)
2 Invalid arguments
3 API error (non-2xx)

Prerequisites

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.

References

Usage Guidance
This skill appears safe to install if you intend to use Parallel FindAll. Before using it, make sure `parallel-cli` is installed from Parallel's official docs, confirm which Parallel account is authenticated, and approve large or pro-tier runs that may use more quota. For large result sets, be aware that the skill may save JSON to /tmp and ask a helper agent to summarize it.
Capability Analysis
Type: OpenClaw Skill Name: parallel-findall Version: 1.0.3 The skill is a legitimate wrapper for the `parallel-cli` tool, designed to interface with the Parallel FindAll API (parallel.ai) for entity discovery. The documentation in SKILL.md provides clear, task-aligned instructions for running searches, polling results, and handling output without any evidence of malicious intent, data exfiltration, or unauthorized command execution.
Capability Assessment
Purpose & Capability
The stated purpose is entity discovery through Parallel FindAll, and the instructions consistently focus on FindAll CLI commands, result formatting, polling, extending, and cancellation.
Instruction Scope
The skill documents external API/CLI operations that may create, poll, extend, or cancel FindAll runs. This is aligned with the purpose, but users should be aware it can consume provider resources or quota.
Install Mechanism
There is no install spec or bundled code, but the skill requires a separately installed and authenticated parallel-cli. Users should install it only from the official Parallel documentation.
Credentials
Using an authenticated Parallel CLI and sending the user's discovery objective to the Parallel service is proportionate to the skill's purpose, but it is still external account/API use.
Persistence & Privilege
For large result sets, the skill suggests saving JSON to /tmp and using sessions_spawn to summarize it. The file path and sub-agent task are bounded, but this is an additional local file and inter-agent data flow.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install parallel-findall
  3. After installation, invoke the skill by name or use /parallel-findall
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.3
parallel-findall 1.0.3 - Clarified SKILL.md documentation for best practices, CLI usage, flags, and prompt guidance. - Added detailed output handling and error code explanations. - Included specific instructions for using FindAll for entity discovery, excluding entities, and managing large result sets. - Improved examples and response format sections for easier onboarding. - Updated references and prerequisites for easier troubleshooting and setup.
Metadata
Slug parallel-findall
Version 1.0.3
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Parallel FindAll?

Discover entities (companies, people, products) matching a natural-language description via the Parallel FindAll API. Use when the user wants to 'find all X'... It is an AI Agent Skill for Claude Code / OpenClaw, with 31 downloads so far.

How do I install Parallel FindAll?

Run "/install parallel-findall" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Parallel FindAll free?

Yes, Parallel FindAll is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Parallel FindAll support?

Parallel FindAll is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Parallel FindAll?

It is built and maintained by NormallyGaussian (@normallygaussian); the current version is v1.0.3.

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