SKILLEMALL.ai

AB kb_literature_review

Produce a focused literature/knowledge review using only selected Research KB contents. Use for query-page tasks asking to write a review, synthesize a topic, compare multiple papers/projects, summarize methods, identify research gaps, or produce a source-grounded thematic survey; accepts Java backend research_kb_agent_task JSON with taskType kb_query or kb_literature_review and returns query-compatible answer/citations.

ClawHub Agent Skills author: myd2002 v1.0.0 MIT-0 9 files · 1 script body ≈ 673 tokens Open the sourceclawhub.ai analyzed 2 d ago

Produce a focused literature/knowledge review using only selected Research KB contents.

As a process B 74/100 · Nearly there — weak spots: failures and branches, consistency, progress reporting

AnalyzerSoftware developmentResearchWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
B
74/100
Nearly there
Failures and branches w 10
0
Progress reporting w 2
0
Consistency w 8
40
the three weakest of ten parameters · all ten

How to improve

    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 · 0

    ✓ No critical or high findings

    Files scanned: 8. 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)

    Process rating: all ten parameters 74/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 40Consistency. Frontmatter name (kb_literature_review) differs from the folder (kb-literature-review)
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 35 steps
    • 100When it triggers. States when to use and when not to
    • 100Execution cost. Instruction body is 673 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 424: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 35 items
    • +3Output format is stated explicitly
    • +4Has examples (2 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

    External checks

    ClawHub: suspicious
    The skill is mostly coherent, but it writes generated review pages into a repository by default using an admin Gitea token, so it needs human review before installation.
    LLM: suspicious (high) · 25 Jun 2026