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CC literature-review

Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or comprehensive literature searches across biomedical, scientific, and technical domains. Creates professionally formatted markdown documents and PDFs with verified citations in multiple citation styles (APA, Nature, Vancouver, etc.).

Not recommendedcritical or high security findings
K-Dense-AI/claude-scientific-writer Agent Skills author: K-Dense-AI 12 files · 5 scripts body ≈ 3 200 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be…

As a process C 50/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerResearchtype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
C
80/100
safety, quality, tests
Safety 60%
76
Quality 40%
86
Run on models
none yet
Process rating
C
50/100
Has gaps
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

The same skill appears in 2 more places: claude-scientific-writer, claude-scientific-writer

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
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.

Broad scope 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 asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
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 · 3

  • high Dangerous commands cmd-pipe-to-shell SKILL.md:224
    Downloads and executes remote code from an unrecognised host (pipe to shell)
    curl -fsSL https://parallel.ai/install.sh | bash
Medium and low: 2
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Read Write Edit Bash
  • low Dangerous commands cmd-autorun-instruction SKILL.md:139
    Instructs the agent to auto-run a script on every session (negated — the text forbids it)
    4. **Unverified citations**: Leads to errors; always run verify_citations.py
    negated

Files scanned: 12. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

✓ No remarks against the Agent Skills spec

Process rating: all ten parameters 50/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 4 mutating operations with no state check
  • 85Steps. 109 steps, 1 vague phrases
  • 100Tools and files. Tools declared in frontmatter
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3200 tokens
  • 100Progress reporting. Reports progress
  • low 11 top-level sections: this looks like several domains in one skill

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
  • -31 of 5 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 480: enough signal without eating the budget
  • +4Structure: 29 headings
  • +3Step-by-step instructions: 109 items
  • +4Has examples (5 code blocks)
  • +4Reference files are cited in the instructions (5 of 5)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.