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BD restssh

Provides access to the MCP_Server_Trigger (v0.1.0) MCP server. It offers 7 tool(s): {"close_ssh_session":"\nFecha uma sessão SSH ativa.\n\nArgs:\n session_id: O ID da sessão a ser fechada.\n","create_ssh_session":"\nCria uma nova sessão SSH explicitamente.\n\nArgs:\n host: Endereço IP ou hostname do dispositivo.\n username: Usuário SSH.\n password: Senha SSH.\n session_id: Identificador único para a nova sessão.\n device_type: Tipo de dispositivo (ex: cisco_ios, linux). Default: cisco_ios.\n port: Porta SSH. Default: 22.\n","execute_ssh_command":"\nExecuta um comando SSH em um dispositivo remoto.\n\nArgs:\n command: O comando a ser executado.\n session_id: ID único da sessão (se não existir, será criada com as credenciais fornecidas).\n host: Endereço IP ou hostname do dispositivo (obrigatório para nova sessão).\n username: Usuário SSH (obrigatório para nova sessão).\n password: Senha SSH (obrigatório para nova sessão).\n device_type: Tipo de dispositivo (ex: cisco_ios, linux, juniper_junos). Default: cisco_ios.\n port: Porta SSH. Default: 22.\n timeout: Timeout opcional para o comando.\n","health_check":"\nVerifica a saúde do serviço API REST SSH.\nRetorna o status atual do serviço.\n","list_active_sessions":"Lista todas as sessões SSH ativas em memória.","list_history_commands":"\nLista o histórico de comandos executados em uma sessão específica.\n\nArgs:\n session_id: O ID da sessão para consultar o histórico.\n","list_history_sessions":"\nLista o histórico de todas as sessões registradas no banco de dados.\nInclui sessões ativas e encerradas.\n"}

modbender/skill-library-mcp Agent Skills author: modbender MIT 2 files body ≈ 659 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Provides access to the MCPServerTrigger (v0.1.0) MCP server. It offers 7 tool(s): {"closesshsession":"\nFecha uma sessão SSH ativa.\n\nArgs:\n sessionid: O ID…

As a process D 49/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches

IntegrationAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
78/100
safety, quality, tests
Safety 60%
100
Quality 40%
46
Run on models
none yet
Process rating
D
49/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. Shorten the description to 1024 characters.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error description-long description is 1624 chars, limit 1024
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note description-budget description takes 1624 of the ~15000-char shared budget for all skills

Process rating: all ten parameters 49/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 1 mutating operations with no state check
  • 40Consistency. Frontmatter name (restssh) differs from the folder (ssh-netmiko)
  • 50When it triggers. No condition that starts the skill
  • 100Tools and files. No external tools needed
  • 100Steps. 11 steps
  • 100Execution cost. Instruction body is 659 tokens
  • low The response is described with custom markup (4 tags): a typed call is more reliable

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 1624: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 8 example trigger phrases
  • +4Structure: 4 headings
  • +3Step-by-step instructions: 11 items
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 46.