📦

botsee

Name: botsee
Author: rivalsee

v0.3.0 Revisión del contenido r1 Riesgo medio 🌐 Acceso a red📁 Acceso al sistema de archivos🔑 Variables de entorno⚙️ Comandos externos

Measure Brand Visibility Across AI Answers

Brands struggle to measure how AI systems mention them and their competitors. BotSee manages research inputs, runs analyses, and turns results into actionable reports.

Compatible con: Claude Codex Code(CC)

⚠️ 50 Deficiente

Instalar con mi Agente

Copia esta solicitud en tu Agente. Incluye la página canónica del Skill y el manifiesto.

Solicitud de agente

Review the Skillstore skill "botsee" from https://skillstore.io/skills/rivalsee-botsee.md and its manifest at https://skillstore.io/api/skills/rivalsee-botsee/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

Tu Agente debe seguir mostrando su plan y solicitar cualquier confirmación exigida por la política de seguridad.

Recursos legibles por agentes

Usa estos enlaces cuando un agente de IA, crawler o script necesite contexto limpio en vez de leer la página completa.

Detalle Markdown GET /skills/rivalsee-botsee.md Manifest firmado GET /api/skills/rivalsee-botsee/manifest Lockfile firmado GET /api/skills/rivalsee-botsee/lockfile

Pruébalo

Usando "botsee". Check the active BotSee site and show the current account balance.

Resultado esperado:

Active site: Example Company. Remaining balance: 4,280 credits. No paid operation was started.

Usando "botsee". Summarize the latest competitor results for the completed analysis.

Resultado esperado:

Acme appears most often across the evaluated responses.
Northstar has the strongest average rank in the enterprise segment.
Three competitors account for most recorded mentions.

Usando "botsee". Generate content from the latest analysis for the selected site.

Resultado esperado:

A blog post was generated from the latest analysis and saved as a timestamped Markdown file. The response also reports credits used.

Auditoría de seguridad

Riesgo medio

v1 • 14/9/2026 Abrir el informe versionado

The skill intentionally contacts the BotSee API, persists local state, and writes generated content. Most high-severity static matches are false positives caused by API-key identifiers, documented config paths, UUID handling, and Markdown backticks. Two medium issues remain: sensitive files are permissioned after creation, and secrets can be passed through command-line arguments.

Archivos escaneados

2,681

Líneas analizadas

Elementos de revisión

Falsos positivos ignorados

Preocupaciones de seguridad confirmadas (2)

Medio

botsee.py:248-253 botsee.py:603-627

Credential files created before restrictive permissions

Two credential-writing paths apply mode 0600 only after writing. On a permissive or preexisting BotSee directory, another local user could briefly read signup tokens or API keys.

Both functions visibly open and write sensitive files before calling chmod. The safer save_user_config path demonstrates that an umask can prevent this creation-time window.

Medio

botsee.py:1826-1827 botsee.py:1847-1848 botsee.py:1856-1860 botsee.py:1868-1881 SKILL.md:155-169

Secrets accepted through command-line arguments

API keys, signup tokens, reset tokens, and payment proofs can be supplied as command arguments. These values may remain in shell history or appear in process listings.

The argparse definitions and usage instructions explicitly place credential-like values after flags. Command arguments commonly persist outside the process receiving them.

Elementos de revisión de capacidades (8)

Estas son capacidades locales reales que pueden esperarse para esta habilidad, por lo que requieren revisión, pero no se cuentan como comportamiento malicioso confirmado.

Medio

botsee.py:181

Python file write/append

with open(USER_CONFIG, "w") as f:

This line writes the BotSee API key and account metadata to the user configuration file. The write is intentional and normally protected by a restrictive umask, but it persists sensitive data.

Medio

botsee.py:199

Python file write/append

with open(WORKSPACE_CONFIG, "w") as f:

This line writes generation settings to .context/botsee-config.json in the current workspace. The data is not secret, but the command has a real workspace modification side effect.

Medio

botsee.py:251

Python file write/append

with open(PENDING_SIGNUP, "w") as f:

This line writes pending signup metadata, including the setup token, to the user home directory. Permissions are tightened only after the write, which creates a brief exposure risk.

Medio

botsee.py:625

Python file write/append

with open(config_path, "w") as f:

This line writes an API key to the user configuration file. The file is changed to mode 0600 afterward, but the credential can briefly inherit broader creation permissions.

Medio

botsee.py:1220

Python file write/append

with open(filename, "w") as f:

This line creates a timestamped Markdown file in the current directory using content returned by the service. It is an intentional output write that can replace a same-named file.

Bajo

botsee.py:113

Python HTTP libraries

req = urllib.request.Request(url, data=body, headers=headers, method=method)

This line constructs outbound BotSee API requests that can include request data and an authorization header. The network use is expected, but it is a real external data transfer.

Bajo

botsee.py:121

Python HTTP libraries

with urllib.request.urlopen(req, timeout=timeout, context=ssl_context) as resp:

This line sends the prepared HTTPS request to the configured BotSee endpoint. Certificate and hostname verification remain enabled, so the network risk is limited and intentional.

Bajo

botsee.py:19

Python environment access

BASE_URL = os.environ.get("BOTSEE_BASE_URL", "https://botsee.io")

The code reads BOTSEE_BASE_URL and uses it as the destination for later authenticated requests. This is intentional configuration, but an untrusted value could redirect API traffic.

Factores de riesgo

🌐 Acceso a red (9)

botsee.py:12 botsee.py:113 botsee.py:121 botsee.py:19 botsee.py:211 botsee.py:342 SKILL.md:84 SKILL.md:123 SKILL.md:559

📁 Acceso al sistema de archivos (29)

🔑 Variables de entorno (50)

⚙️ Comandos externos (50)

SKILL.md:69-71 SKILL.md:71-78 SKILL.md:78-80 SKILL.md:80-83 SKILL.md:83-85 SKILL.md:85-107 SKILL.md:107-116 SKILL.md:116-118 SKILL.md:118-119 SKILL.md:119-122 SKILL.md:122-124 SKILL.md:124-131 SKILL.md:131-136 SKILL.md:136-138 SKILL.md:138-146 SKILL.md:146-149 SKILL.md:149-152 SKILL.md:152 SKILL.md:153 SKILL.md:155-156 SKILL.md:156-160 SKILL.md:160-166 SKILL.md:166-168 SKILL.md:168 SKILL.md:169-173 SKILL.md:173-175 SKILL.md:175-177 SKILL.md:177-181 SKILL.md:181-183 SKILL.md:183-187 SKILL.md:187-191 SKILL.md:191-197 SKILL.md:197-199 SKILL.md:199 SKILL.md:200-204 SKILL.md:204-206 SKILL.md:206-208 SKILL.md:208-211 SKILL.md:211-212 SKILL.md:212-213 SKILL.md:213-221 SKILL.md:221-223 SKILL.md:223-227 SKILL.md:227-229 SKILL.md:229-233 SKILL.md:233-235 SKILL.md:235-241 SKILL.md:241-243 SKILL.md:243-245 SKILL.md:245-253

Auditado por: codex

Compartir y citar este informe

Comparte el informe de evaluación versionado, la insignia neutral, la tarjeta insertable y las citas. Skillstore presenta evidencias sin decidir si este Skill es seguro.

Abrir el informe versionado

Copiar enlace del informe

https://skillstore.io/skills/rivalsee-botsee/audits/1?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

Insignia Markdown

[![Skillstore security assessment](https://skillstore.io/badges/skills/rivalsee-botsee/security.svg)](https://skillstore.io/skills/rivalsee-botsee?utm_source=security_passport_badge)

Insignia HTML

<a href="https://skillstore.io/skills/rivalsee-botsee?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/rivalsee-botsee/security.svg" alt="Skillstore security assessment" loading="lazy"></a>

Tarjeta para insertar

<iframe src="https://skillstore.io/embed/skills/rivalsee-botsee.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>

Citas académicas (APA · BibTeX · CFF)

Cita APA

rivalsee. (2026). botsee security audit report (audit version 1) [Author version 0.3.0]. Skillstore. https://skillstore.io/skills/rivalsee-botsee/audits/1

Cita BibTeX

@techreport{rivalsee-rivalsee-botsee-2026,
  author = {rivalsee},
  title = {botsee security audit report (audit version 1)},
  institution = {Skillstore},
  year = {2026},
  number = {1},
  url = {https://skillstore.io/skills/rivalsee-botsee/audits/1},
  note = {Author version 0.3.0}
}

CITATION.cff

cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "botsee security audit report (audit version 1)"
version: "0.3.0"
type: report
authors:
  - name: "rivalsee"
date-released: "2026-09-14"
url: "https://skillstore.io/skills/rivalsee-botsee/audits/1"
identifiers:
  - type: other
    value: "skillstore:rivalsee-botsee:audit:1"
    description: "Skillstore immutable audit report identifier"

Puntuación de Skillstore

Por qué esta puntuación Confianza de la evidencia: Medio

Arquitectura

100

Mantenibilidad

Contenido

Comunidad

Cumplimiento de la especificación

Lo que puedes crear

Track brand visibility

Measure brand appearances, ranking, competitors, keywords, and cited sources across supported AI answer providers.

Build audience research

Create customer types, personas, and buyer questions before running a structured visibility analysis.

Automate competitive reporting

Run analyses, retrieve detailed results, inspect credit usage, and generate content from agent workflows.

Prueba estos prompts

Check account status

Check my BotSee account status, active site, remaining credits, and available next actions. Do not start any paid operation.

Set up a research site

Create a BotSee site for [DOMAIN] with [TYPE_COUNT] customer types, [PERSONA_COUNT] personas per type, and [QUESTION_COUNT] questions per persona.

Run and summarize analysis

Run a BotSee analysis for [SITE_UUID]. Summarize leading competitors, recurring keywords, cited sources, and remaining credits after completion.

Compare detailed findings

Analyze [SITE_UUID] using [MODELS] and [SCOPE]. Retrieve responses, competitors, keywords, sources, and recommendations, then identify three evidence-backed priorities.

Mejores prácticas

Check the active site and credit balance before starting analysis or generation.
Use explicit site and analysis identifiers when several projects are active.
Review generated content and recommendations before publishing or applying them.

Evitar

Do not place live API keys, reset tokens, or payment proofs in shared prompts or logs.
Do not retry create commands blindly because repeated calls can create duplicate resources.
Do not start paid analysis or generation without confirming the site, scope, and expected credit use.

Preguntas frecuentes

What does this skill measure?

It uses BotSee to measure brand mentions, competitors, rankings, keywords, sources, and AI responses.

Which AI tools can use this skill?

The report declares support for Claude, Codex, and Claude Code.

Does the skill require a BotSee account?

Yes. Most operations require a BotSee API key, network access, and available credits.

Where are credentials stored?

The skill stores the API key and active site in ~/.botsee/config.json.

Does analysis finish immediately?

No. The command polls BotSee until completion and can wait for up to ten minutes.

Does the skill write project files?

Yes. It writes workspace configuration and saves generated blog content as a timestamped Markdown file.

Detalles del desarrollador

Autor

rivalsee

Licencia

MIT

Versión del autor

v0.3.0

Revisión de Skillstore

Repositorio

https://github.com/rivalsee/botsee-skill/tree/4a0f13a79c2ac6fd93c72b7d06275d8350951bac/skills/botsee

Ref.

42d356d060430b424cc46118d00a354afa5575c1

Actualidad del mantenimiento

14/9/2026

Uso

0 descargas · 0 vistas

Estructura de archivos

📄 botsee.py

📄 SKILL.md