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AC literature-review

Finds, ranks and reads the literature on a question, the retrieval loop the lead runs itself over OpenAlex, arXiv, Crossref, PubMed and bioRxiv with a fixed budget, deduplication, ranking by topical fit, reading of the load-bearing papers and claim-level links, for related-work sections, prior-art checks, surveys and systematic reviews. Use for "find papers", "what is known about", related work, or a review; escalate to PRISMA screening only when a systematic review is requested. For one quick fact or definition use research-lookup.

synthetic-sciences/OpenScience Agent Skills author: synthetic-sciences Apache-2.0 3 files body ≈ 1 556 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Finds, ranks and reads the literature on a question, the retrieval loop the lead runs itself over OpenAlex, arXiv, Crossref, PubMed and bioRxiv with a fixed…

As a process C 58/100 · 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
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
C
58/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "summary"
    • note frontmatter-key unknown frontmatter key "role"

    Process rating: all ten parameters 58/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 2 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 19 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1556 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +2Single-language instructions
    • +5Description quotes 2 example trigger phrases
    • +3Description length 538: enough signal without eating the budget
    • +4Structure: 5 headings
    • +3Step-by-step instructions: 19 items
    • +4Reference files are cited in the instructions (2 of 2)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.