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parallel-findall

Preis unbestätigt★ 77 GitHub-StarsVerzeichnis aktualisiert · 26. Sept. 2026agent-skill

Übersicht

Discover entities (companies, people, products, etc.) matching a natural-language description. Use when the user asks to 'find all X' or 'list every Y that…' — e.g., 'Find AI startups that raised Series A in 2026', 'List roofing companies in Charlotte NC', 'Show me YC W24 dev tools companies'. Different from web-search (which returns webpages) and deep-research (which returns a narrative report). Use this when the user wants a structured list of entities.

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FindAll: Entity Discovery

Find: $ARGUMENTS

Full FindAll requires parallel-cli ≥ 0.3.0; the optional entity-search path requires ≥ 0.6.0. If a documented command or option is missing, update through the installation method used for this CLI, then retry. See https://docs.parallel.ai/integrations/cli.

When to use this skill

Use FindAll for a structured list of entities matching a description. Use parallel-web-search for webpages or quick answers, parallel-deep-research for narrative analysis, and parallel-data-enrichment to add fields to a list the user already has.

Default to the comprehensive, asynchronous findall run. It supports match conditions, exclusions, enrichment, evidence, and entity types beyond companies and people. “Find all” does not guarantee exhaustive internet coverage.

Use the synchronous entity-search path only when the user explicitly wants a quick or rough list of companies or people and accepts results without individual verification. Do not choose it just because the entity type is supported. It has no exclusions, generator selection, enrichment, or FindAll condition/enrichment citations.

Step 1: Start and retain the run

Choose an unused, descriptive, run-specific $FILENAME for the saved JSON files. Pass the user's objective as one quoted argument, without shell evaluation.

parallel-cli findall run "$ARGUMENTS" --no-wait --json -o "/tmp/$FILENAME-create.json"

Defaults are generator core and match limit 10. Use -n 50 for up to 50 matched entities; the allowed limit is 5–1000. Stay with core unless the user requests a different tradeoff. pro searches a larger pool and is slower/costlier; base is a faster, lower-quality option for an explicitly requested rough scan. Spot-check specific claims such as batch, year, and geography against available evidence, especially for base.

For requested exclusions:

parallel-cli findall run "$ARGUMENTS" --no-wait --json \
    --exclude '[{"name":"Google","url":"google.com"},{"name":"OpenAI","url":"openai.com"}]' \
    -o "/tmp/$FILENAME-create.json"

If the objective needs clarification, parallel-cli findall ingest "$ARGUMENTS" --json previews the inferred entity type, conditions, and suggested enrichments. This calls the API; it is not an offline or free test. Refine the objective before creating the run if the inferred conditions differ from the user's intent.

Capture the returned findall_id immediately, along with the objective, generator, match limit and exclusions. Report that the run started and give a monitoring URL only if one was actually returned. Do not infer a URL or a guaranteed completion time. If the creation response is lost, resolve the existing job before submitting again.

Step 2: Add requested fields explicitly

--no-wait ingests and creates the run but does not apply suggested enrichments. Requested output fields such as CEO name or employee count need a separate enrichment request; mentioning them in the objective is insufficient.

parallel-cli findall enrich "$FINDALL_ID" \
    '{"type":"object","properties":{"ceo":{"type":"string","description":"CEO name"},"employee_count":{"type":"number","description":"Number of employees"}}}' \
    -p core --json

Use a JSON Schema object describing the user's fields, not the complete ingest envelope. Retain the exact submitted schema and processor locally with the run ID, including multiple requests if used. Do not rely on schema summaries to reconstruct them later. Enrichment adds non-boolean output data; it does not change match conditions.

Enrichment can be added while the run is active or after completion. A terminal run can requeue to process the fields. Creation, enrichment acceptance, and populated results are separate outcomes. Do not claim the fields are ready from the enrichment response or a completed poll alone.

Step 3: Check status and retrieve results

parallel-cli findall status "$FINDALL_ID" --json
parallel-cli findall poll "$FINDALL_ID" -o "/tmp/$FILENAME.json" --timeout 60
parallel-cli findall result "$FINDALL_ID" -o "/tmp/$FILENAME-snapshot.json"

Use bounded waits. A timeout (exit 5) or interrupt is local wait exhaustion, not cancellation. Check status and resume the same ID while it is active, within the user's waiting window; do not submit another run. The shared poller does not recognize the compatibility status action_required. If that status, failed, cancelled, or an inactive unfinished state appears, stop automatic waiting and report the state and saved ID as needing attention.

result returns a snapshot and does not prove completion. Read status and is_active together. After enrichment, inspect each matched candidate's output for every requested field. If fields are missing, take further result snapshots within a bounded waiting window, even if the first poll said completed. Report missing, null, or failed values rather than inventing them; if the window expires, return partial results and the ID for resumption. An empty matched set is not proof of successful enrichment.

Avoid --json for large result sets; -o retains the complete JSON. These commands can overwrite their selected files, so use paths belonging to this run. Preserve the raw candidate list and status. /tmp is temporary; copy requested deliverables to a persistent user location when needed.

Present matches and evidence

Present only candidates with match_status: "matched" as matches. Preserve generated, unmatched, and discarded candidates in the raw file. Review obvious query-echo placeholders and unsupported entries rather than treating every candidate as an entity.

Review URLs in the context of the entity. LinkedIn profiles can legitimately identify people, and YC or Crunchbase profiles can identify companies. Do not discard these solely because the entity does not own the domain. Flag missing or unverifiable URLs and use available evidence to resolve uncertainty.

Use condition and enrichment basis for factual claims, with its source URLs. The entity's primary URL and a supporting citation may differ. Do not label a primary/profile URL as evidence for an attribute unless it supports the claim.

Lead with the number of matched entities presented, note exclusions or unresolved entries, and use a table or list with names, URLs, and requested fields. Include the saved raw-results path, run ID, current state, and any incomplete fields. Sparse or noisy results can warrant suggesting a revised objective or generator; do not automatically create a replacement paid run.

Get more matches

Extend only when the user requests additional matches:

parallel-cli findall schema "$FINDALL_ID" --json
parallel-cli findall extend "$FINDALL_ID" 50 --json

50 is an increment, not the new total. Check the known creation limit or current schema, including prior extensions, so the resulting total stays at or below 1000. Preview runs cannot be extended. A completed run is eligible only if its termination reason was match_limit_met; status/result in the CLI omit that reason and cannot prove eligibility. For an explicitly requested extension within the limit, let the API validate eligibility and surface any rejection without creating a new run automatically.

Retain the updated limit and poll the same ID for new results. Recheck requested enrichment fields; if the existing enrichment must be reapplied, use the original retained request payload and processor within the user's authorized scope.

Fast entity search

Use only for explicit speed/rough-list intent and entity type companies or people. It is synchronous and returns entity_set_id plus ranked entities, not findall_id or verified candidates.

parallel-cli findall entity-search "$ARGUMENTS" -t companies -n 10 -o "/tmp/$FILENAME.json"

The -n limit is 5–1000, default 10. Choose a limit proportional to the user's request. Avoid highly restrictive criteria on this path: relevance can decline toward the tail. Use full FindAll when individual condition checks or enrichment are required.

Keep legitimate directory/profile links and review empty URLs or query-echo names. Present these as unverified leads, cite their links as links to the entities, and avoid attributing absent FindAll basis or verification to them. Report the saved path and returned count. Never pass an entity_set_id to FindAll poll/status/result/enrich/extend. If the user later requests those capabilities, explain that a separate full run is needed and retain the original quick results.

Setup

Requires an installed and authenticated parallel-cli. Check parallel-cli --version and parallel-cli auth --json; auth can exit successfully while authenticated is false. Missing binary, unsupported command/option, and authentication failure need different remedies: installation, upgrade through the existing installation method, or terminal login respectively. See https://docs.parallel.ai/integrations/cli. Stop the affected request on auth failure, do not ask for secrets in chat, and do not change account policy to work around blocked setup.

Quelle ansehen ↗

Dateimetadaten

name: parallel-findall
description: "Discover entities (companies, people, products, etc.) matching a natural-language description. Use when the user asks to 'find all X' or 'list every Y that…' — e.g., 'Find AI startups that raised Series A in 2026', 'List roofing companies in Charlotte NC', 'Show me YC W24 dev tools companies'. Different from web-search (which returns webpages) and deep-research (which returns a narrative report). Use this when the user wants a structured list of entities."
user-invocable: true
argument-hint: <objective describing entities to find>
compatibility: Requires parallel-cli >= 0.6.0 and internet access.
allowed-tools: Bash(parallel-cli:*)
metadata:
  author: parallel

Originaltext anzeigen

---
name: parallel-findall
description: "Discover entities (companies, people, products, etc.) matching a natural-language description. Use when the user asks to 'find all X' or 'list every Y that…' — e.g., 'Find AI startups that raised Series A in 2026', 'List roofing companies in Charlotte NC', 'Show me YC W24 dev tools companies'. Different from web-search (which returns webpages) and deep-research (which returns a narrative report). Use this when the user wants a structured list of entities."
user-invocable: true
argument-hint: <objective describing entities to find>
compatibility: Requires parallel-cli >= 0.6.0 and internet access.
allowed-tools: Bash(parallel-cli:*)
metadata:
author: parallel
---

# FindAll: Entity Discovery

Find: $ARGUMENTS

> Full FindAll requires `parallel-cli` ≥ 0.3.0; the optional `entity-search` path requires ≥ 0.6.0. If a documented command or option is missing, update through the installation method used for this CLI, then retry. See <https://docs.parallel.ai/integrations/cli>.

## When to use this skill

Default to the comprehensive, asynchronous `findall run`. It supports match conditions, exclusions, enrichment, evidence, and entity types beyond companies and people. “Find all” does not guarantee exhaustive internet coverage.

Use the synchronous `entity-search` path only when the user explicitly wants a quick or rough list of companies or people and accepts results without individual verification. Do not choose it just because the entity type is supported. It has no exclusions, generator selection, enrichment, or FindAll condition/enrichment citations.

## Step 1: Start and retain the run

Choose an unused, descriptive, run-specific `$FILENAME` for the saved JSON files. Pass the user's objective as one quoted argument, without shell evaluation.

```bash
parallel-cli findall run "$ARGUMENTS" --no-wait --json -o "/tmp/$FILENAME-create.json"
```

Defaults are generator `core` and match limit `10`. Use `-n 50` for up to 50 matched entities; the allowed limit is 5–1000. Stay with `core` unless the user requests a different tradeoff. `pro` searches a larger pool and is slower/costlier; `base` is a faster, lower-quality option for an explicitly requested rough scan. Spot-check specific claims such as batch, year, and geography against available evidence, especially for `base`.

For requested exclusions:

```bash
parallel-cli findall run "$ARGUMENTS" --no-wait --json \
--exclude '[{"name":"Google","url":"google.com"},{"name":"OpenAI","url":"openai.com"}]' \
-o "/tmp/$FILENAME-create.json"
```

If the objective needs clarification, `parallel-cli findall ingest "$ARGUMENTS" --json` previews the inferred entity type, conditions, and suggested enrichments. This calls the API; it is not an offline or free test. Refine the objective before creating the run if the inferred conditions differ from the user's intent.

Capture the returned `findall_id` immediately, along with the objective, generator, match limit and exclusions. Report that the run started and give a monitoring URL only if one was actually returned. Do not infer a URL or a guaranteed completion time. If the creation response is lost, resolve the existing job before submitting again.

## Step 2: Add requested fields explicitly

`--no-wait` ingests and creates the run but does **not** apply suggested enrichments. Requested output fields such as CEO name or employee count need a separate enrichment request; mentioning them in the objective is insufficient.

```bash
parallel-cli findall enrich "$FINDALL_ID" \
'{"type":"object","properties":{"ceo":{"type":"string","description":"CEO name"},"employee_count":{"type":"number","description":"Number of employees"}}}' \
-p core --json
```

## Step 3: Check status and retrieve results

```bash
parallel-cli findall status "$FINDALL_ID" --json
parallel-cli findall poll "$FINDALL_ID" -o "/tmp/$FILENAME.json" --timeout 60
parallel-cli findall result "$FINDALL_ID" -o "/tmp/$FILENAME-snapshot.json"
```

Use bounded waits. A timeout (exit 5) or interrupt is local wait exhaustion, not cancellation. Check status and resume the same ID while it is active, within the user's waiting window; do not submit another run. The shared poller does not recognize the compatibility status `action_required`. If that status, `failed`, `cancelled`, or an inactive unfinished state appears, stop automatic waiting and report the state and saved ID as needing attention.

`result` returns a snapshot and does not prove completion. Read `status` and `is_active` together. After enrichment, inspect each matched candidate's `output` for every requested field. If fields are missing, take further result snapshots within a bounded waiting window, even if the first poll said completed. Report missing, null, or failed values rather than inventing them; if the window expires, return partial results and the ID for resumption. An empty matched set is not proof of successful enrichment.

Avoid `--json` for large result sets; `-o` retains the complete JSON. These commands can overwrite their selected files, so use paths belonging to this run. Preserve the raw candidate list and status. `/tmp` is temporary; copy requested deliverables to a persistent user location when needed.

## Present matches and evidence

Present only candidates with `match_status: "matched"` as matches. Preserve generated, unmatched, and discarded candidates in the raw file. Review obvious query-echo placeholders and unsupported entries rather than treating every candidate as an entity.

## Get more matches

Extend only when the user requests additional matches:

```bash
parallel-cli findall schema "$FINDALL_ID" --json
parallel-cli findall extend "$FINDALL_ID" 50 --json
```

`50` is an increment, not the new total. Check the known creation limit or current schema, including prior extensions, so the resulting total stays at or below 1000. Preview runs cannot be extended. A completed run is eligible only if its termination reason was `match_limit_met`; status/result in the CLI omit that reason and cannot prove eligibility. For an explicitly requested extension within the limit, let the API validate eligibility and surface any rejection without creating a new run automatically.

## Fast entity search

Use only for explicit speed/rough-list intent and entity type `companies` or `people`. It is synchronous and returns `entity_set_id` plus ranked `entities`, not `findall_id` or verified candidates.

```bash
parallel-cli findall entity-search "$ARGUMENTS" -t companies -n 10 -o "/tmp/$FILENAME.json"
```

The `-n` limit is 5–1000, default 10. Choose a limit proportional to the user's request. Avoid highly restrictive criteria on this path: relevance can decline toward the tail. Use full FindAll when individual condition checks or enrichment are required.

Keep legitimate directory/profile links and review empty URLs or query-echo names. Present these as unverified leads, cite their links as links to the entities, and avoid attributing absent FindAll basis or verification to them. Report the saved path and returned count. Never pass an `entity_set_id` to FindAll poll/status/result/enrich/extend. If the user later requests those capabilities, explain that a separate full run is needed and retain the original quick results.

## Setup

Requires an installed and authenticated `parallel-cli`. Check `parallel-cli --version` and `parallel-cli auth --json`; auth can exit successfully while `authenticated` is false. Missing binary, unsupported command/option, and authentication failure need different remedies: installation, upgrade through the existing installation method, or terminal login respectively. See <https://docs.parallel.ai/integrations/cli>. Stop the affected request on auth failure, do not ask for secrets in chat, and do not change account policy to work around blocked setup.

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Lizenz: MIT
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Vor Installation prüfen: Automatische Installation vermeiden

Lizenz: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
Financial research output is not financial advice; require human review before any live investment decision
KI-Prüffreigabe fehlt
Financial research output is not financial advice; require human review before any live investment decision.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 77 GitHub stars
Stars/forks activity: 77 stars, 10 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution
Review status: AI review approval is missing

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Tools sind Metadatenhinweise, keine getestete Kompatibilität. Prompts sind Vorschläge.

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1Quelle lesen und Eingaben, Ergebnisse, Abhängigkeiten sowie Berechtigungen prüfen.
2Agent um einen Plan bitten. Einrichtung und Kosten vor einem isolierten Test genehmigen.
3Ergebnisse und geänderte Dateien prüfen. Nur tatsächliche Ausführungen melden und die Quellrevision aufbewahren.

Prüfe Abhängigkeiten, API-Schlüssel und externe Kosten in der Quelle. Öffentliche Repositories bedeuten nicht, dass alle Dienste kostenlos sind.

Quelle und Nutzungshinweise

ErfasstStatisch geprüft

Metadaten und Prüfungen dienen der Orientierung. Beliebtheit, Quellenerfassung und erfolgreiche Ausführung sind verschiedene Fakten.

Quell-Repository: parallel-web/parallel-agent-skills
Lizenz: MIT
Version: Unknown
Letzter GitHub-Push: 25. Sept. 2026
Verzeichnis aktualisiert: 26. Sept. 2026
Anleitungspfad: skills/parallel-findall/SKILL.md @ 8fc1fc426e79

Version aus den Verzeichnismetadaten; Releases der Quelle prüfen.

Qualität

60/100

Vielversprechend

Vertrauen

61/100

Nur Sandbox

Audit

73/100

Prüfung nötig

Vollständiges Audit öffnen Eval-Bericht ansehen

Dependency or permission surface needs review
Permission surface may require sandboxing
Financial research output is not financial advice; require human review before any live investment decision
KI-Prüffreigabe fehlt
Financial research output is not financial advice; require human review before any live investment decision.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 77 GitHub stars
Stars/forks activity: 77 stars, 10 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution
Review status: AI review approval is missing

Verified installs: —
Ergebnisse: —

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Weitere Details

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    "description": "Discover entities (companies, people, products, etc.) matching a natural-language description. Use when the user asks to 'find all X' or 'list every Y that…' — e.g., 'Find AI startups that raised Series A in 2026', 'List roofing companies in Charlotte NC', 'Show me YC W24 dev tools companies'. Different from web-search (which returns webpages) and deep-research (which returns a narrative report). Use this when the user wants a structured list of entities.",
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      "install": "npx skills add parallel-web/parallel-agent-skills --skill parallel-findall",
      "installSafety": "standard package or runtime install path",
      "permissionSurface": "secrets or environment access, shell or command execution",
      "documentation": "Strong README/SKILL.md context",
      "agentOutcomes": "No agent outcome data yet"
    },
    "outcome_evidence": {
      "total": 0,
      "successes": 0,
      "failures": 0,
      "not_relevant": 0,
      "success_rate": null,
      "recent_success_rate": null,
      "recent_failure_rate": null,
      "install_attempts": 0,
      "install_success_rate": null,
      "risk_blocked": 0,
      "setup_required": 0,
      "avg_output_quality": null,
      "production_outcomes": 0,
      "last_outcome_at": null,
      "label": "No agent outcome data yet"
    },
    "auto_install": {
      "allowed": false,
      "sandbox_required": true,
      "reason": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
    },
    "best_for": [
      "research",
      "agent-skill"
    ],
    "known_risks": [
      "AI review approval is missing",
      "Financial research output is not financial advice; require human review before any live investment decision.",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "GitHub adoption: 77 GitHub stars",
      "Stars/forks activity: 77 stars, 10 forks; issue activity unavailable in current metadata",
      "Dependency/runtime risk: command execution surface, credential or environment access",
      "Permission surface: secrets or environment access, shell or command execution"
    ]
  },
  "agent_proven": {
    "version": "agent-proven-v1",
    "score": 0,
    "tier": "unproven",
    "label": "Needs first agent run",
    "summary": "No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.",
    "metrics": {
      "totalOutcomes": 0,
      "successfulOutcomes": 0,
      "failedOutcomes": 0,
      "installAttempts": 0,
      "installSuccessRate": null,
      "successRate": null,
      "recentSuccessRate": null,
      "recentFailureRate": null,
      "riskBlocked": 0,
      "setupRequired": 0,
      "notRelevant": 0,
      "avgOutputQuality": null,
      "avgTimeToUsefulMs": null,
      "productionOutcomes": 0,
      "humanReviewRequired": 0,
      "uniqueAgents": 0,
      "lastOutcomeAt": null
    },
    "signals": [],
    "penalties": [
      "No real agent outcome evidence yet"
    ]
  },
  "audit": {
    "score": 73,
    "risk_level": "needs_review",
    "risk_label": "Needs review",
    "warnings": [
      "Dependency or permission surface needs review",
      "Permission surface may require sandboxing",
      "Financial research output is not financial advice; require human review before any live investment decision",
      "AI review approval is missing",
      "Financial research output is not financial advice; require human review before any live investment decision.",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "GitHub adoption: 77 GitHub stars"
    ]
  },
  "safety_gate": {
    "tier": "blocked",
    "label": "Blocked for auto-install",
    "auto_install_policy": "block",
    "auto_install_allowed": false,
    "human_review_required": true,
    "blocked": true,
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
  },
  "quality": {
    "score": 60,
    "label": "Promising"
  },
  "supply": {
    "track": "Research and knowledge work",
    "scenario": "Research agents",
    "maintenance": "16d since push",
    "risk": "Needs review"
  },
  "alternative_skills": [
    {
      "slug": "yanliudesign-mono-color-skill",
      "name": "mono-color",
      "url": "https://www.openagentskill.com/skills/yanliudesign-mono-color-skill",
      "stars": 1919,
      "install_command": "npx skills add yanliudesign/mono-color-skill --skill mono-color",
      "trust_score": 83,
      "audit_score": 90
    },
    {
      "slug": "assafelovic-gpt-researcher",
      "name": "GPT Researcher",
      "url": "https://www.openagentskill.com/skills/assafelovic-gpt-researcher",
      "stars": 29542,
      "install_command": "",
      "trust_score": 85,
      "audit_score": 90
    }
  ],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "high-compliance environments without internal security review",
    "No major risk signals from current metadata",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "Financial research output is not financial advice; require human review before any live investment decision",
    "AI review approval is missing"
  ],
  "agent_contract": {
    "task_input": "Use parallel-findall in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 69/100 Manual review",
      "Audit: 73/100 Needs review",
      "Safety: 29/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "parallel-web-parallel-findall (parallel-findall)",
      "install_command": "npx skills add parallel-web/parallel-agent-skills --skill parallel-findall",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "parallel-web-parallel-findall",
      "task": "Use parallel-findall in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/parallel-web-parallel-findall",
    "api": "https://www.openagentskill.com/api/agent/skills/parallel-web-parallel-findall",
    "audit": "https://www.openagentskill.com/skills/parallel-web-parallel-findall/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=parallel-web-parallel-findall&task=Use%20parallel-findall%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20parallel-findall%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20parallel-findall%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/parallel-web-parallel-findall/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/parallel-web-parallel-findall"
  }
}

Für Ersteller

Quelle des Eintrags

Registry-indexiert

Beanspruchbar

Dieser Eintrag wurde aus öffentlichen Quellen indexiert und ist erst nach Genehmigung eines Maintainer-Anspruchs offiziell.

Ersteller: parallel
Quelle: parallel-web/parallel-agent-skills
Indexiert von: OpenAgentSkill Community-Index

Die Zuordnung verlinkt auf das öffentliche Repository oder Creator-Profil. Creator können den Eintrag beanspruchen, um Eigentümersignale zu aktualisieren.

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