Research Prior Art

Prior Art Research and Cataloging

Search for, evaluate, and catalog prior art relevant to an research project.

Context

Prior art research is primarily performed during the Exploration phase but can happen at any point — including mid-iteration when a hypothesis demands additional context. The goal is to build a curated catalog of existing work so the researcher can stand on the shoulders of others rather than reinvent the wheel or miss known pitfalls.

Source Types

Search across these categories, prioritized by typical relevance to research:

1. Academic papers and preprints — search arXiv, IEEE, ACM, USENIX

proceedings. Focus on security, software engineering, and PL venues.

1. CVE databases and vulnerability advisories — NVD, MITRE CVE, vendor

advisories. Especially relevant when researching specific vulnerability classes.

1. Security conference talks — Black Hat, DEF CON, OffensiveCon, HITB,

REcon, CCC. Check published slides and video archives.

1. Open-source tools and projects — GitHub, GitLab. Look for existing

implementations addressing the same or adjacent problem.

1. Blog posts and write-ups — Project Zero, security research blogs,

vendor engineering blogs. Often contain practical insights missing from papers.

1. Standards and specifications — RFCs, OWASP guides, NIST publications.

Relevant when the research touches protocol or compliance boundaries.

Procedure

Step 1 — Identify the research project

Locate the research project directory and read brief.md to understand the research question, problem domain, scope boundaries, and any prior art already noted in the brief.

Step 2 — Derive search queries

From the brief, generate a set of search queries. Use multiple query strategies:

• Direct queries: keywords from the research question itself.
• Synonym expansion: alternative terminology for the same concepts

(e.g., "fuzzing" / "fuzz testing" / "generative testing").

• Problem-adjacent queries: related problems that may have transferable

solutions (e.g., when researching API endpoint discovery, also search for "web crawler coverage," "JavaScript static analysis," "SPA route extraction").

• Author/group tracking: if a known research group works in the area,

search for their recent publications.

Present the generated queries to the researcher for validation and adjustment before executing searches.

Step 3 — Execute searches

Search across the source types listed above. For each result:

1. Retrieve the title, authors/creators, publication date, and source URL.
2. Read or skim the abstract/summary/README.
3. Write a 1–2 sentence annotation summarizing what it contributes to the

research question.

1. Assign a relevance rating:

• High — directly addresses the research question or a core hypothesis.
• Medium — relevant to the problem domain but does not directly answer

the question.

• Low — tangentially related; useful for background context only.

Step 4 — Detect duplicates

Before adding entries, check prior-art.md for existing entries with the same URL or substantially similar title. Skip duplicates; update annotations if the existing entry can be improved.

Step 5 — Update the catalog

Append new entries to the table in prior-art.md. Maintain the sequential numbering. Each entry must contain:

| Field | Description | |---|---| | # | Sequential number | | Source | Clickable title linking to the URL | | Type | Paper / CVE / Tool / Talk / Blog / Standard / Other | | Annotation | 1–2 sentences on what this source contributes | | Relevance | High / Medium / Low |

Step 6 — Summarize findings

After cataloging, provide the researcher with a brief summary:

• Total new entries added, broken down by type.
• Top 3–5 most relevant sources with a sentence each on why they matter.
• Any notable gaps: areas where prior art is surprisingly scarce or absent,

which may indicate unexplored territory or indicate the need for different search terms.

• Suggested adjustments to the research question or hypotheses based on

what was found.

Step 7 — Update the brief (if needed)

If the prior art search reveals information that should update the brief's "Prior art (summary)" section or suggests changes to the research question or scope, propose specific edits to brief.md for the researcher's approval.

Tips for Effective Prior Art Search

• Recency bias: Domain moves fast. Prioritize sources from the last 3–5

years, but don't ignore foundational work.

• Negative results matter: papers or posts describing failed approaches

are valuable — they help avoid known dead ends.

• Implementation vs. theory: for each paper, note whether a reference

implementation exists. A paper with code is significantly more useful for hypothesis formulation.

• Citation chains: when a highly relevant paper is found, check its

references and who cites it for additional leads.

Relation to Other Skills

• Typically invoked after research-init during the Exploration phase.
• Findings often feed directly into research-hypothesis (first hypotheses

are informed by gaps in prior art).

• Can be re-invoked at any point during iterations when additional context

is needed.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: v0lka
• Source: v0lka/skills
• License: MIT

Install and usage instructions live in the source repository linked above.