literature-survey

literature-survey is a Literature review & citations skill for AI agents, published by gaasher in the Agent-Loop-Skills repository on GitHub. Skillspace rates literature-survey D (59/100) and it passed the safety scan; the rating is based on static analysis only.

Use when the user wants a structured, saturating literature survey on a question — not a one-shot summary, but an evidence/contradiction matrix (sources × claims) built by iterative search until coverage stops growing. Each round expands the search (new sub-topic queries plus citation-graph walks), admits new sources, extracts their claims with verbatim snippets, and records where every source stands on each claim (supports / contradicts / qualifies); the feedback signal is how many new matrix-changing sources a round adds, and it stops at saturation, patience, or budget. The output is the matrix plus a synthesis of consensus, disputes, and gaps, every cell backed by a real citation. Not for grading a written proposal against the literature (that is a proposal-evaluation task) and not for generating new hypotheses — this maps what the literature already says.

Grade

D

Quality

59 / 100

Safety

Passed

GitHub stars

132

Unproven: rated by static analysis only, not yet compared head-to-head.

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