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BF Semantic Scholar Search

Search for academic papers, get detailed paper information, author profiles, and citation data through Semantic Scholar API. This skill provides comprehensive academic literature search capabilitie...

modbender/skill-library-mcp Agent Skills author: modbender MIT 4 files body ≈ 969 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Search for academic papers, get detailed paper information, author profiles, and citation data through Semantic Scholar API.

As a process F 39/100 · Will not run — References files that are not bundled: ../sci-data-extractor/, ../pubmed-search-skill/, ../sci-hub-search-skill/

IntegrationResearchtype 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
80/100
safety, quality, tests
Safety 60%
95
Quality 40%
58
Run on models
none yet
Process rating
F
39/100
Will not run
References files that are not bundled: ../sci-data-extractor/, ../pubmed-search-skill/, ../sci-hub-search-skill/
Tools and files w 18
0
Inputs and preconditions w 11
0
Failures and branches w 10
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.

Dangerous commands 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 skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

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. The text references files that are not there: add them or drop the references.
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 Dangerous commands cmd-pipe-to-shell-known-host README.md:60
    Pipe-to-shell installer from a well-known host (still executes remote code)
    curl -LsSf https://astral.sh/uv/install.sh | sh

Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: ../sci-data-extractor/
  • warning missing-ref reference to a missing file: ../pubmed-search-skill/
  • warning missing-ref reference to a missing file: ../sci-hub-search-skill/

Process rating: all ten parameters 39/100

Will not run. References files that are not bundled: ../sci-data-extractor/, ../pubmed-search-skill/, ../sci-hub-search-skill/
  • 0Tools and files. 3 referenced file(s) missing: ../sci-data-extractor/, ../pubmed-search-skill/, ../sci-hub-search-skill/
  • 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
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (Semantic Scholar Search) differs from the folder (semanticscholar-search-skill)
  • 60Result and completion. Output format stated, no completion criterion
  • 100Steps. 14 steps
  • 100Execution cost. Instruction body is 969 tokens
  • 100Running it twice. No mutating operations

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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 200: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 14 items
  • +3Output format is stated explicitly
  • +4Has examples (7 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 58.