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BC supportforge-api

AI-powered customer support automation using SupportForge API - customer support, help desk, ticket routing, auto-reply, automated responses, customer service, support ticket management, knowledge base integration, chatbot responses, FAQ automation, support escalation, customer inquiry handling, live chat automation, support workflow, helpdesk automation, customer care, technical support, issue resolution, support analytics, ticket classification, response templates, multi-channel support, customer communication, support agent assistance, and intelligent customer service automation.

ClawHub Agent Skills author: Jbennett111 v1.0.0 2 files body ≈ 2 517 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationCustomer supporttype 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
86/100
safety, quality, tests
Safety 60%
95
Quality 40%
72
Run on models
none yet
Process rating
C
56/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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.
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 · 5

✓ No critical or high findings

Medium and low: 5
  • low Secrets in code secret-password-literal SKILL.md:46
    Hard-coded password / key literal (may be an example) (placeholder value)
    -H "X-API-Key: sf_a…890" \
    placeholder
  • low Secrets in code secret-password-literal SKILL.md:87
    Hard-coded password / key literal (may be an example) (placeholder value)
    -H "X-API-Key: sf_a…890" \
    placeholder
  • low Secrets in code secret-password-literal SKILL.md:114
    Hard-coded password / key literal (may be an example) (placeholder value)
    -H "X-API-Key: sf_a…890" \
    placeholder
  • low Secrets in code secret-password-literal SKILL.md:146
    Hard-coded password / key literal (may be an example) (placeholder value)
    -H "X-API-Key: sf_a…890" \
    placeholder
  • low Secrets in code secret-password-literal SKILL.md:181
    Hard-coded password / key literal (may be an example) (placeholder value)
    -H "X-API-Key: sf_a…890" \
    placeholder

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

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 56/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 100Tools and files. No external tools needed
  • 100Steps. 23 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2517 tokens

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

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 589: enough signal without eating the budget
  • +4Structure: 26 headings
  • +3Step-by-step instructions: 23 items
  • +4Has examples (20 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: clean
This is a coherent SupportForge API helper, but it can send customer support data and an API key to a third-party service.
LLM: benign (high) · VirusTotal: · 29 May 2026