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squirrelscan

Harga belum dikonfirmasi★ 87 Star GitHubDirektori diperbarui · 6 Okt 2026agent-skill

Ringkasan

squirrelscan audits websites for SEO, performance, security, accessibility, content, and structured data issues (260+ rules) and scores site health, via the squirrel CLI. Use when the user wants to check, audit, or improve a website's SEO, ranking, speed, or health, and for anything squirrelscan itself, installing or updating the CLI, login and API keys, running audits, publishing and sharing reports, cloud credits, MCP server setup, configuration, or troubleshooting.

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Dokumentasi sumber, bukan instruksi untuk situs ini. Periksa izin sebelum menjalankan perintah.

squirrelscan CLI

squirrelscan is a website audit tool built for AI agents. It answers "what's wrong with this website and how do I fix it": it crawls a site like a search engine, analyzes every page against 260+ rules in 21 categories (SEO, performance, security, accessibility, content, structured data, agent readiness, and more), and returns a health score plus concrete, fixable issues. Use it whenever a user wants their site checked, ranked better, faster, or healthier, before/after a deploy, or in CI.

It ships as a single CLI binary, squirrel, for macOS, Windows, and Linux. This skill covers operating it: installing, authenticating, running audits, publishing reports, cloud features, and MCP integration. For the full fix-the-website workflow (audit, map issues to code, fix, re-audit), use the companion audit-website skill.

Install

Download and install instructions: squirrelscan.com/download

The binary installs to ~/.local/bin/squirrel. Verify with:

squirrel --version

Keep it current:

squirrel self update

If squirrel is not found, ensure ~/.local/bin is in PATH, or reinstall from the download page.

Command overview

Command	Purpose
`squirrel audit <url>`	Crawl + analyze + report in one step
`squirrel crawl <url>`	Crawl only (no analysis)
`squirrel analyze`	Run audit rules on a stored crawl
`squirrel report [id]`	Query, render, diff, and publish stored reports
`squirrel init`	Create `squirrel.toml` project config
`squirrel config`	Show or edit configuration
`squirrel auth`	login / logout / status / whoami
`squirrel keys`	Mint, list, revoke org API keys
`squirrel credits`	Cloud credit balance + feature pricing
`squirrel mcp`	Run the local MCP server (stdio)
`squirrel skills`	Install or update agent skills
`squirrel self`	install / update / doctor / completion / version / settings / uninstall
`squirrel feedback`	Send feedback to the squirrelscan team

Every command supports --help.

Quickstart

squirrel init -n my-project        # optional: project config in cwd
squirrel audit https://example.com --format llm

Local audits are free and run entirely on your machine. No account needed.
Use --format llm when an agent is reading the output: it is a compact, token-optimized format built for LLMs.
Audits are cached in a local project database; squirrel report re-renders without re-crawling.

Coverage modes

Mode	Default pages	Behavior
`quick` (default)	25	Seed + sitemaps only, fast health check
`surface`	100	One sample per URL pattern (`/blog/{slug}` crawled once)
`full`	500	Crawl everything up to the limit

squirrel audit https://example.com -C full -m 500 --format llm

Authentication and accounts

Local audits never require an account. Sign in to unlock cloud features (publishing, browser rendering, scheduled crawls, credits):

squirrel auth login      # browser-based login
squirrel auth status     # source, scopes, active org
squirrel auth whoami
squirrel auth logout

Headless / CI environments use an org API key instead:

squirrel keys create     # requires a login session; prints an sq_... key

Set it as SQUIRRELSCAN_API_KEY in the environment. Treat keys as secrets; never commit them.

Reports

Render the latest (or a specific) stored audit:

squirrel report --list                 # recent audits
squirrel report <audit-id> --format llm
squirrel report example.com --format markdown -o report.md

Formats: console, text, json, html, markdown, xml, llm. Filter with --severity error or --category core,links.

Publishing

Signed-in audits publish a shareable report to reports.squirrelscan.com by default (visibility: unlisted). Control it:

squirrel report <audit-id> --publish --visibility unlisted   # public | unlisted | private
squirrel audit https://example.com --no-publish              # skip publishing for a run
squirrel audit https://example.com --offline                 # fully offline: no cloud, no publish, no telemetry

Regression diffs

squirrel report --diff <baseline-audit-id> --format llm
squirrel report --regression-since example.com --format llm

Diff mode supports console, text, json, llm, and markdown.

Cloud features and credits

Cloud features are pay-as-you-go with credits (nothing charged up front). Check balance and pricing:

squirrel credits

--render / --render-mode auto|all|off: cloud browser rendering for client-rendered pages (uses credits, requires login).
--yes skips spend confirmations up to the configured per-audit credit cap.
--fail-on "score<90" (repeatable) makes CI runs exit non-zero when a threshold trips.
The dashboard at app.squirrelscan.com shows audit history, issues, and credit usage.

MCP server

Two ways to connect agents over MCP:

Local (stdio): squirrel mcp runs against the local CLI. Register it in your agent's MCP config with command squirrel and args ["mcp"].
Hosted (streamable-http): https://mcp.squirrelscan.com/mcp. Sign in via OAuth from the MCP client, or send an Authorization: Bearer sq_... API key header.

Docs: https://docs.squirrelscan.com/developers/mcp

Agent feedback

Call the send_feedback tool any time something in a session surprises you. It takes category, message, and optional run_id/website_id. Pick the category that fits:

bug_report — a defect in squirrelscan itself: a wrong or missing rule result, a crash, a broken tool. Include the site, rule id, and what you expected.
feature_request — something squirrelscan should do but doesn't.
what_worked — something worked well and you want the team to know.
confusing — a response or behavior was unclear.
missing_data — a report or tool response lacked something you needed.
tool_ergonomics — awkward tool shape, arguments, or naming.
other — anything else.

Feedback lands directly in the team's review queue with your org attached. It works with any authenticated credentials, including read-only API keys, and is available on the hosted MCP surface now (not yet on squirrel mcp local stdio). Use it instead of squirrel feedback when you're an agent reporting mid-session; humans can use squirrel feedback or squirrelscan.com/support.

Configuration

Project config lives in squirrel.toml (created by squirrel init). User settings live at ~/.squirrel/settings.json.

squirrel config show
squirrel config set <key> <value>
squirrel config path
squirrel config validate

Useful sections: [crawler] (delays, headers, incremental re-crawl), [cloud] (render mode, max credits per audit).

Custom request headers

Attach headers to every crawl request with the repeatable -H "Name: Value" flag or a headers map under [crawler]. The main use case is Web Bot Auth (Shopify / Cloudflare), so platforms that block unknown crawlers can authorize squirrelscan. Header values are secrets: squirrelscan redacts them in output, and you should source them from a secret store rather than committing them. Full recipe: https://docs.squirrelscan.com/guides/web-bot-auth

Maintenance

squirrel self doctor       # health checks
squirrel self update       # update the binary
squirrel self completion   # shell completions
squirrel skills update     # update installed agent skills

Troubleshooting

squirrel: command not found: install from squirrelscan.com/download and ensure ~/.local/bin is in PATH.
Session expired / 401: run squirrel auth login again, or check SQUIRRELSCAN_API_KEY.
Slow or stuck crawl: add --verbose to see progress; large sites can take minutes.
Invalid URL: include the protocol: https://example.com, not example.com.
Anything else: run squirrel self doctor, then report it — agents via the send_feedback MCP tool (bug_report category), humans via squirrel feedback or squirrelscan.com/support.

Lihat sumber ↗

Metadata berkas

name: squirrelscan
description: squirrelscan audits websites for SEO, performance, security, accessibility, content, and structured data issues (260+ rules) and scores site health, via the squirrel CLI. Use when the user wants to check, audit, or improve a website's SEO, ranking, speed, or health, and for anything squirrelscan itself, installing or updating the CLI, login and API keys, running audits, publishing and sharing reports, cloud credits, MCP server setup, configuration, or troubleshooting.
license: See LICENSE file in repository root
compatibility: Requires squirrel CLI installed and accessible in PATH (or guides the user to install it)
metadata:
  author: squirrelscan
  version: "1.2"
allowed-tools: Bash(squirrel:*) Read

Lihat teks asli

---
name: squirrelscan
description: squirrelscan audits websites for SEO, performance, security, accessibility, content, and structured data issues (260+ rules) and scores site health, via the squirrel CLI. Use when the user wants to check, audit, or improve a website's SEO, ranking, speed, or health, and for anything squirrelscan itself, installing or updating the CLI, login and API keys, running audits, publishing and sharing reports, cloud credits, MCP server setup, configuration, or troubleshooting.
license: See LICENSE file in repository root
compatibility: Requires squirrel CLI installed and accessible in PATH (or guides the user to install it)
metadata:
  author: squirrelscan
  version: "1.2"
allowed-tools: Bash(squirrel:*) Read
---

# squirrelscan CLI

squirrelscan is a website audit tool built for AI agents. It answers "what's wrong with this website and how do I fix it": it crawls a site like a search engine, analyzes every page against 260+ rules in 21 categories (SEO, performance, security, accessibility, content, structured data, agent readiness, and more), and returns a health score plus concrete, fixable issues. Use it whenever a user wants their site checked, ranked better, faster, or healthier, before/after a deploy, or in CI.

It ships as a single CLI binary, `squirrel`, for macOS, Windows, and Linux. This skill covers operating it: installing, authenticating, running audits, publishing reports, cloud features, and MCP integration. For the full fix-the-website workflow (audit, map issues to code, fix, re-audit), use the companion `audit-website` skill.

## Links

- Website: [squirrelscan.com](https://squirrelscan.com)
- Docs: [docs.squirrelscan.com](https://docs.squirrelscan.com)
- Rule reference: `https://docs.squirrelscan.com/rules/{rule_category}/{rule_id}`
- Dashboard (cloud account, audit history, credits): [app.squirrelscan.com](https://app.squirrelscan.com)

## Install

Download and install instructions: [squirrelscan.com/download](https://squirrelscan.com/download)

The binary installs to `~/.local/bin/squirrel`. Verify with:

```bash
squirrel --version
```

Keep it current:

```bash
squirrel self update
```

If `squirrel` is not found, ensure `~/.local/bin` is in PATH, or reinstall from the download page.

## Command overview

| Command | Purpose |
|---------|---------|
| `squirrel audit <url>` | Crawl + analyze + report in one step |
| `squirrel crawl <url>` | Crawl only (no analysis) |
| `squirrel analyze` | Run audit rules on a stored crawl |
| `squirrel report [id]` | Query, render, diff, and publish stored reports |
| `squirrel init` | Create `squirrel.toml` project config |
| `squirrel config` | Show or edit configuration |
| `squirrel auth` | login / logout / status / whoami |
| `squirrel keys` | Mint, list, revoke org API keys |
| `squirrel credits` | Cloud credit balance + feature pricing |
| `squirrel mcp` | Run the local MCP server (stdio) |
| `squirrel skills` | Install or update agent skills |
| `squirrel self` | install / update / doctor / completion / version / settings / uninstall |
| `squirrel feedback` | Send feedback to the squirrelscan team |

Every command supports `--help`.

## Quickstart

```bash
squirrel init -n my-project        # optional: project config in cwd
squirrel audit https://example.com --format llm
```

- Local audits are free and run entirely on your machine. No account needed.
- Use `--format llm` when an agent is reading the output: it is a compact, token-optimized format built for LLMs.
- Audits are cached in a local project database; `squirrel report` re-renders without re-crawling.

### Coverage modes

| Mode | Default pages | Behavior |
|------|---------------|----------|
| `quick` (default) | 25 | Seed + sitemaps only, fast health check |
| `surface` | 100 | One sample per URL pattern (`/blog/{slug}` crawled once) |
| `full` | 500 | Crawl everything up to the limit |

```bash
squirrel audit https://example.com -C full -m 500 --format llm
```

## Authentication and accounts

Local audits never require an account. Sign in to unlock cloud features (publishing, browser rendering, scheduled crawls, credits):

```bash
squirrel auth login      # browser-based login
squirrel auth status     # source, scopes, active org
squirrel auth whoami
squirrel auth logout
```

Headless / CI environments use an org API key instead:

```bash
squirrel keys create     # requires a login session; prints an sq_... key
```

Set it as `SQUIRRELSCAN_API_KEY` in the environment. Treat keys as secrets; never commit them.

## Reports

Render the latest (or a specific) stored audit:

```bash
squirrel report --list                 # recent audits
squirrel report <audit-id> --format llm
squirrel report example.com --format markdown -o report.md
```

Formats: `console`, `text`, `json`, `html`, `markdown`, `xml`, `llm`. Filter with `--severity error` or `--category core,links`.

### Publishing

Signed-in audits publish a shareable report to reports.squirrelscan.com by default (visibility: unlisted). Control it:

```bash
squirrel report <audit-id> --publish --visibility unlisted   # public | unlisted | private
squirrel audit https://example.com --no-publish              # skip publishing for a run
squirrel audit https://example.com --offline                 # fully offline: no cloud, no publish, no telemetry
```

### Regression diffs

```bash
squirrel report --diff <baseline-audit-id> --format llm
squirrel report --regression-since example.com --format llm
```

Diff mode supports `console`, `text`, `json`, `llm`, and `markdown`.

## Cloud features and credits

Cloud features are pay-as-you-go with credits (nothing charged up front). Check balance and pricing:

```bash
squirrel credits
```

- `--render` / `--render-mode auto|all|off`: cloud browser rendering for client-rendered pages (uses credits, requires login).
- `--yes` skips spend confirmations up to the configured per-audit credit cap.
- `--fail-on "score<90"` (repeatable) makes CI runs exit non-zero when a threshold trips.
- The dashboard at [app.squirrelscan.com](https://app.squirrelscan.com) shows audit history, issues, and credit usage.

## MCP server

Two ways to connect agents over MCP:

- **Local (stdio)**: `squirrel mcp` runs against the local CLI. Register it in your agent's MCP config with command `squirrel` and args `["mcp"]`.
- **Hosted (streamable-http)**: `https://mcp.squirrelscan.com/mcp`. Sign in via OAuth from the MCP client, or send an `Authorization: Bearer sq_...` API key header.

Docs: https://docs.squirrelscan.com/developers/mcp

### Agent feedback

Call the `send_feedback` tool any time something in a session surprises you. It takes `category`, `message`, and optional `run_id`/`website_id`. Pick the category that fits:

- `bug_report` — a defect in squirrelscan itself: a wrong or missing rule result, a crash, a broken tool. Include the site, rule id, and what you expected.
- `feature_request` — something squirrelscan should do but doesn't.
- `what_worked` — something worked well and you want the team to know.
- `confusing` — a response or behavior was unclear.
- `missing_data` — a report or tool response lacked something you needed.
- `tool_ergonomics` — awkward tool shape, arguments, or naming.
- `other` — anything else.

Feedback lands directly in the team's review queue with your org attached. It works with any authenticated credentials, including read-only API keys, and is available on the hosted MCP surface now (not yet on `squirrel mcp` local stdio). Use it instead of `squirrel feedback` when you're an agent reporting mid-session; humans can use `squirrel feedback` or [squirrelscan.com/support](https://squirrelscan.com/support).

## Configuration

Project config lives in `squirrel.toml` (created by `squirrel init`). User settings live at `~/.squirrel/settings.json`.

```bash
squirrel config show
squirrel config set <key> <value>
squirrel config path
squirrel config validate
```

Useful sections: `[crawler]` (delays, headers, incremental re-crawl), `[cloud]` (render mode, max credits per audit).

### Custom request headers

Attach headers to every crawl request with the repeatable `-H "Name: Value"` flag or a `headers` map under `[crawler]`. The main use case is Web Bot Auth (Shopify / Cloudflare), so platforms that block unknown crawlers can authorize squirrelscan. Header values are secrets: squirrelscan redacts them in output, and you should source them from a secret store rather than committing them. Full recipe: https://docs.squirrelscan.com/guides/web-bot-auth

## Maintenance

```bash
squirrel self doctor       # health checks
squirrel self update       # update the binary
squirrel self completion   # shell completions
squirrel skills update     # update installed agent skills
```

## Troubleshooting

- **`squirrel: command not found`**: install from [squirrelscan.com/download](https://squirrelscan.com/download) and ensure `~/.local/bin` is in PATH.
- **Session expired / 401**: run `squirrel auth login` again, or check `SQUIRRELSCAN_API_KEY`.
- **Slow or stuck crawl**: add `--verbose` to see progress; large sites can take minutes.
- **Invalid URL**: include the protocol: `https://example.com`, not `example.com`.
- **Anything else**: run `squirrel self doctor`, then report it — agents via the `send_feedback` MCP tool (`bug_report` category), humans via `squirrel feedback` or [squirrelscan.com/support](https://squirrelscan.com/support).

Tinjau sumber

Harga dan biaya penggunaan

Dapatkan skill: Harga belum dikonfirmasi
Jalankan: Persyaratan belum dikonfirmasi. Periksa biaya agen, API, dan layanan di sumbernya.
Lisensi: See LICENSE file in repository root
Harga belum dikonfirmasi: Harga belum dikonfirmasi. Tautan sumber dan instalasi yang ada tetap tersedia.

Gratis diperoleh bukan berarti gratis dijalankan. Harga bukan penilaian keamanan. Kirim informasi harga →

Sumber perlu ditinjau

Sumber berubah atau gagal disinkronkan. Tinjau sumber terbaru sebelum memasang.

Tinjau sebelum memasang: Hindari pemasangan otomatis

Lisensi: See LICENSE file in repository root

Dependency or permission surface needs review
Permission surface may require sandboxing
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 87 GitHub stars
Stars/forks activity: 87 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

Buka audit lengkap

Daftar alat adalah petunjuk metadata, bukan kompatibilitas teruji. Prompt adalah saran.

Mulai dengan tugas kecil

1Baca sumber dan pastikan masukan, keluaran, dependensi, serta izin.
2Minta rencana dari agent. Setujui pengaturan dan biaya sebelum uji terisolasi.
3Periksa hasil dan berkas yang berubah. Laporkan hanya yang dijalankan dan simpan revisi sumber.

Periksa dependensi, kunci API, dan biaya layanan pihak ketiga pada sumber. Repositori publik tidak berarti semua layanan gratis.

Sumber dan catatan penggunaan

Terindeks

Metadata dan tinjauan bersifat saran. Popularitas, penemuan sumber, dan keberhasilan eksekusi adalah fakta berbeda.

Repositori sumber: squirrelscan/skills
Lisensi: See LICENSE file in repository root
Versi: 1.0.0
Push GitHub terakhir: 6 Sep 2026
Direktori diperbarui: 6 Okt 2026
Jalur instruksi: skills/squirrelscan/SKILL.md @ f4219bcd69da

Versi dilaporkan dalam metadata direktori; periksa rilis sumber.

Kualitas

63/100

Menjanjikan

Kepercayaan

60/100

Hanya sandbox

Audit

73/100

Perlu ditinjau

Buka audit lengkap Lihat laporan evaluasi

Dependency or permission surface needs review
Permission surface may require sandboxing
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 87 GitHub stars
Stars/forks activity: 87 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

Verified installs: —
Hasil: —

Menyalin bukan memasang. Jumlah instalasi memerlukan laporan berhasil dan bukan jaminan kualitas menyeluruh.

Akses agent

API Registry menyediakan sinyal keputusan, kepercayaan, audit, use case, dan pemasangan tanpa mengikis UI.

Buka API pemasangan Format teks LLM Buka Manifest Rencana resolusi otomatis

Detail lainnya

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    "category": "security",
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    "handoff_url": "https://www.openagentskill.com/api/skills/squirrelscan-squirrelscan-5044009e/install",
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      "Permission surface needs review: secrets or environment access, shell or command execution",
      "GitHub adoption: 87 GitHub stars",
      "Stars/forks activity: 87 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",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "GitHub adoption: 87 GitHub stars",
      "Stars/forks activity: 87 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"
    ]
  },
  "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": 63,
    "label": "Promising"
  },
  "supply": {
    "track": "Marketing and growth automation",
    "scenario": "Content automation",
    "maintenance": "1mo since push",
    "risk": "Needs review"
  },
  "alternative_skills": [
    {
      "slug": "projectdiscovery-nuclei",
      "name": "Nuclei",
      "url": "https://www.openagentskill.com/skills/projectdiscovery-nuclei",
      "stars": 29159,
      "install_command": "",
      "trust_score": 91,
      "audit_score": 91
    },
    {
      "slug": "wazuh-wazuh",
      "name": "Wazuh",
      "url": "https://www.openagentskill.com/skills/wazuh-wazuh",
      "stars": 16271,
      "install_command": "",
      "trust_score": 88,
      "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",
    "Quality score needs review",
    "Permission surface needs review: secrets or environment access, shell or command execution"
  ],
  "agent_contract": {
    "task_input": "Use squirrelscan 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: 68/100 Manual review",
      "Audit: 73/100 Needs review",
      "Safety: 25/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "squirrelscan-squirrelscan-5044009e (squirrelscan)",
      "install_command": "",
      "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": "squirrelscan-squirrelscan-5044009e",
      "task": "Use squirrelscan 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/squirrelscan-squirrelscan-5044009e",
    "api": "https://www.openagentskill.com/api/agent/skills/squirrelscan-squirrelscan-5044009e",
    "audit": "https://www.openagentskill.com/skills/squirrelscan-squirrelscan-5044009e/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=squirrelscan-squirrelscan-5044009e&task=Use%20squirrelscan%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20squirrelscan%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20squirrelscan%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/squirrelscan-squirrelscan-5044009e/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/squirrelscan-squirrelscan-5044009e"
  }
}

Untuk kreator

Sumber listing

Diindeks Registry

Dapat diklaim

Listing ini diindeks dari sumber publik dan belum ditandai resmi hingga klaim pemelihara disetujui.

Kreator: squirrelscan
Sumber: squirrelscan/skills
Diindeks oleh: Indeks komunitas OpenAgentSkill

Atribusi menautkan ke repositori publik atau profil kreator. Kreator dapat mengklaim listing untuk memperbarui sinyal kepemilikan.

Klaim skill ini

Klaim pemilik

Klaim listing skill ini

Listing Diindeks Registry ini dikaitkan dengan squirrelscan, tetapi belum ditandai resmi. Klaim untuk menambahkan sinyal pemilik terverifikasi dan membuat pembaruan peluncuran, pemasangan, serta audit berikutnya lebih tepercaya.

Kit berbagi

Kit backlink kreator

Tambahkan badge bukti ke README Anda

Tampilkan listing kanonis, sinyal kepercayaan dan audit saat ini, serta bukti Agent-Proven nyata di tempat pengembang mengevaluasi repositori.

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/squirrelscan-squirrelscan-5044009e?metric=listed&label=Listed)](https://www.openagentskill.com/skills/squirrelscan-squirrelscan-5044009e?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/squirrelscan-squirrelscan-5044009e?metric=trust&label=Trust)](https://www.openagentskill.com/skills/squirrelscan-squirrelscan-5044009e?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/squirrelscan-squirrelscan-5044009e?metric=audit&label=Audit)](https://www.openagentskill.com/skills/squirrelscan-squirrelscan-5044009e/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/squirrelscan-squirrelscan-5044009e?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/squirrelscan-squirrelscan-5044009e?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)

Pratinjau badge Buka audit Kit kreator

Sinyal komunitas

Bagikan apakah skill ini bermanfaat untuk alur kerja Agent Anda. Masukan gabungan meningkatkan peringkat dari waktu ke waktu.