SKILLEMALL.ai

BF multi-domain-search

Search 8 knowledge domains in one query — live web, 250M academic papers, 150M scholarly works, arXiv preprints, 36M biomedical papers, chemical compounds, government datasets, and dictionary. Goes beyond web search into academic, scientific, and public data via x402.

ClawHub Agent Skills author: Plag v1.0.0 MIT-0 4 files · 1 script body ≈ 1 632 tokens Open the sourceclawhub.ai analyzed 31 h ago

Search 8 knowledge domains in one query — live web, 250M academic papers, 150M scholarly works, arXiv preprints, 36M biomedical papers, chemical compounds…

As a process F 32/100 · Will not run — weak spots: steps, result and completion, inputs and preconditions

ReferenceResearchtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
84/100
safety, quality, tests
Safety 60%
95
Quality 40%
68
Run on models
none yet
Process rating
F
32/100
Will not run
Steps w 15
0
Result and completion w 14
0
Inputs and preconditions w 11
0
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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Exfiltration net-credential-use skills/search.sh:37
    Credential used in a network call (verify the destination is the intended service)
    CURL_ARGS+=(-H "Authorization: Bearer ${RESEARCH_API_KEY}")

Files scanned: 4. 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")
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 32/100

  • 0Steps. Prose only: no discrete steps
  • 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
  • 30Running it twice. 2 mutating operations with no state check
  • 40Consistency. Frontmatter name (multi-domain-search) differs from the folder (multi-search-skill)
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 100Execution cost. Instruction body is 1632 tokens
  • 100Progress reporting. Reports progress

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)
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 268: enough signal without eating the budget
  • +4Structure: 13 headings
  • +4Has examples (19 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.

External checks

ClawHub: clean
This is a disclosed paid research-search skill that sends queries to an external gateway and does not show hidden persistence, destructive behavior, or unrelated data access.
LLM: benign (high) · VirusTotal: · 8 Jun 2026