reference-corpus-analyzer

Reference Corpus Analyzer

Synthesize a literature corpus into a structured comparison matrix. This skill answers: across these N papers, who does what, how do they differ, and where is the open space?

Use this skill when:

related-work writing requires a side-by-side method comparison across multiple papers
you want to identify the closest 3–5 papers and understand exactly how they differ from each other
a literature survey needs trend identification across publication years or venues
you want to map open gaps across a set of existing approaches before writing the related-work section
you have 5+ source cards and want a comparison table rather than individual summaries

Do not use this skill to create per-paper source cards — use reference-reading-summarizer for that. Do not use this skill to link a paper to your project's claims — use reference-project-synthesizer for that. Use this skill after source cards exist; avoid re-reading raw PDFs unless a card is insufficient.

Pair this skill with:

reference-reading-summarizer upstream: produce source cards before running corpus analysis
reference-project-synthesizer upstream or downstream: link individual papers to project memory before or after comparison
related-work-positioning-writer downstream: use the comparison matrix to write novelty-boundary paragraphs
baseline-selection-audit downstream: use the ranking to identify must-have baselines
literature-review-sprint when the corpus is not yet assembled and a broader topic survey is needed first

Skill Directory Layout

<installed-skill-dir>/
├── SKILL.md
└── templates/
    └── comparison-matrix.md

Progressive Loading

Read reference/cards/ to find available source cards before reading raw sources.
Read reference/.agent/source-index.md or reference/.agent/reference-index.md to get the corpus inventory.
Read memory/claim-board.md when the comparison should be anchored to specific project claims.
Read templates/comparison-matrix.md before writing the output matrix.

Core Principles

Tiered depth: read deeply only the top-N closest papers; skim the rest for placement.
The comparison matrix is a project artifact, not a free-text essay — it should be queryable.
Ranking closest work requires a clear criterion: task overlap, method overlap, or claim overlap.
Gaps should be stated specifically: "no paper does X under constraint Y" beats "X is underexplored".
Do not invent paper properties not stated in the source card or the paper itself.

Step 1 — Assemble the Corpus

Read reference/.agent/source-index.md (or reference-index.md) to list available sources.

For each source, record:

source ID and title
card availability: has-card, no-card, partial-card
initial relevance estimate: core, related, background, tangential

If cards are missing for sources that appear highly relevant, route to reference-reading-summarizer first.

Step 2 — Select Tiered Read Depth

Assign read depth to each source:

Tier	Sources	Read depth
Deep	Top 3–5 closest by task + method overlap	Full source card; re-read raw source if card is insufficient
Standard	Next 5–10 related works	Source card only
Survey	Remaining background papers	Title + abstract + card summary

Criterion for "closest": same task, same claim type, overlapping method family, or shared benchmark.

Step 3 — Build the Comparison Matrix

Read templates/comparison-matrix.md.

Dimensions to compare (select those relevant to the project):

Task / problem: what problem does the paper address?
Method family: what is the core mechanism (attention, diffusion, RL, prompting, etc.)?
Key innovation: what is the single thing this paper claims to contribute?
Benchmark / dataset: what is it evaluated on?
Primary metric: what metric is reported?
Best reported result: the headline number (with venue and year for context)
Limitations acknowledged: what does the paper say it cannot do?
Relationship to our work: closer / complementary / orthogonal / superseded by ours

For each tier-1 (deep) paper, also add:

Closest claim to ours: the specific claim that most overlaps with our paper's contribution
Key differentiator: in one sentence, how our work differs from this paper

Save to reference/corpus-analysis-<date>.md.

Step 4 — Rank Closest Work

Produce a ranked list of the top-5 closest papers with:

Rank: 1
Paper: [title] ([venue year])
Overlap: task=high / method=medium / claim=high
Closest claim: [their specific claim that overlaps ours]
Differentiator: [one sentence: how we differ]
Novelty risk: high / medium / low
Reviewer action: cite as closest work / cite as baseline / cite as background

A paper with novelty risk: high and method=high overlap is the paper whose related-work paragraph needs the clearest boundary statement.

Step 5 — Identify Gaps and Trends

Gaps: what combinations of (task, method, constraint, benchmark) are not yet addressed by any paper in the corpus?

Gap: no paper addresses [X] under [constraint Y] with [method family Z]
Evidence: papers A, B, C address X but not under Y; papers D, E address Y but not X
Opportunity: our work fills this gap by [brief description]

Trends (optional, for survey mode):

Which method families are gaining / losing papers over the last 3 years?
Which benchmarks are becoming standard vs. falling out of use?
What claims were controversial 2 years ago and are now accepted?

Step 6 — Write Memory Writeback

Update reference/.agent/source-index.md with read-depth assignments
Update memory/risk-board.md for any high-novelty-risk closest-work findings
Update memory/claim-board.md if the comparison changes the novelty framing of a claim
The comparison matrix itself is saved in reference/ — do not copy it into memory/

Final Sanity Check

Before finishing:

tier-1 papers have been read at full card depth
the comparison matrix has consistent dimensions across all papers
top-5 closest-work ranking has differentiators in one sentence each
gaps are stated specifically (not as vague "future work" language)
novelty-risk papers are flagged for related-work-positioning-writer