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Generate more revenue with high-quality leads. Give your AI agent direct access to Prospairrow — extract prospects, enrich with deep company insights, discover competitors, and generate content marketing. Fuel your sales pipeline with enriched firmographics, tech stacks, and key contacts so your team can build a pipeline that closes faster.

ClawHub Agent Skills author: discry v1.2.5 42 files · 1 script body ≈ 901 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions

GeneratorInfrastructureAI 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
82/100
safety, quality, tests
Safety 60%
90
Quality 40%
69
Run on models
none yet
Process rating
C
59/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
50
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

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 · 6

✓ No critical or high findings

Medium and low: 6
  • medium Exfiltration net-redirectable-api-key src/sites/prospairrow/tasks/_api.ts:73
    Helper sends the API key to a host configured by an environment variable — the key can be redirected to another server
    API key + configurable base URL from environment
  • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:31
    High-entropy token-like string (may be an id, hash or a credential)
    resolution: {integrity: sha5…7pY+zoMV…h0x/Ptw8…8dg==}
  • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:43
    High-entropy token-like string (may be an id, hash or a credential)
    resolution: {integrity: sha5…b00+Gxjx…zRc/oZwU…hzA==}
  • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:61
    High-entropy token-like string (may be an id, hash or a credential)
    resolution: {integrity: sha512-vHk/hA7/1Ack…wbo+jaSh…Gtl+A5zq…HFg==}
  • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:73
    High-entropy token-like string (may be an id, hash or a credential)
    resolution: {integrity: sha5…Dsc+j03S…0oA==}
  • low Secrets in code secret-high-entropy-token pnpm-lock.yaml:175
    High-entropy token-like string (may be an id, hash or a credential)
    resolution: {integrity: sha5…NS8+tHW7…WOF+PEzk…X4Q==}

Files scanned: 42. 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 59/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (web, git, node) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 30 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 901 tokens
  • 100Running it twice. No mutating operations
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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
  • -2localhost URLs: will not work for another user
  • -45 reference files, but SKILL.md never points to them: the model will not open them
  • +1No license
  • +2Single-language instructions
  • +3Description length 342: enough signal without eating the budget
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 30 items
  • +4Has examples (3 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.

External checks

ClawHub: suspicious
The skill is not malicious, but it needs review because it handles live Prospairrow credentials and some supposedly read-only scoring actions can still make account-affecting POST calls.
LLM: suspicious (high) · VirusTotal: benign · 28 May 2026