Install
$ agentstack add skill-fcakyon-phd-skills-literature-research ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Literature Research Methodology
You are helping a researcher conduct systematic literature research. Follow this methodology to ensure thorough, accurate coverage.
Step 1: Scope Definition
Before searching:
- Clarify the exact research question or topic boundary
- Identify key terms and their synonyms (e.g., "content moderation" = "safety filtering" = "NSFW detection")
- Define inclusion/exclusion criteria (year range, venue type, methodology type)
- Ask if the user has seed papers to start from
Step 2: Systematic Search
Use multiple search strategies in order:
2a. Direct Search
- Search for the topic using key terms via web search
- Target: Google Scholar, Semantic Scholar, arXiv, DBLP
- Vary search terms to catch different framings of the same concept
2b. Citation Chaining
From seed papers or initial results:
- Forward chaining: who cited this paper? (find via Semantic Scholar or Google Scholar)
- Backward chaining: what does this paper cite? (read its references)
- This catches papers that use different terminology but address the same problem
2c. Venue Mining
- Identify top venues for the topic (conferences, journals, workshops)
- Check recent proceedings of these venues for relevant papers
- Workshop papers often contain early-stage work not yet in main conferences
2d. Open Source Discovery
- Search GitHub for implementations related to the topic
- Check Papers With Code for the specific task/dataset
- Look for "awesome-X" lists curated by the community
Step 3: Categorization
Organize found papers into a structured taxonomy:
| Paper | Year | Venue | Approach | Key Result | Code? | Relevance |
|-------|------|-------|----------|-----------|-------|-----------|
Group by methodology or approach type, not chronologically.
Step 4: Gap Identification
Map what exists vs. what's missing:
- Coverage matrix: rows = problem aspects, columns = existing approaches
- Empty cells = potential gaps
- For each candidate gap:
- Search specifically for work filling this gap (it may exist under different terms)
- Check very recent papers (last 6 months) that might have addressed it
- Assess whether the gap is meaningful (would filling it advance the field?)
Step 5: Gap Validation
For each identified gap, verify it's real:
- [ ] Searched with at least 3 different phrasings
- [ ] Checked proceedings of top-3 venues from last 2 years
- [ ] No preprint on arXiv addressing this gap
- [ ] The gap is technically feasible to address
- [ ] Filling the gap would be a meaningful contribution
Rate confidence: HIGH (extensively searched, clearly missing), MEDIUM (searched but might have missed niche work), LOW (limited search, gap may exist elsewhere).
Step 6: Output Format
Produce a structured research landscape:
- Topic summary — 2-3 sentence overview of the research area
- Paper table — categorized list with year, venue, approach, results, code availability
- Gap table — identified gaps with confidence levels and evidence
- Recommended readings — top 5-10 most relevant papers for the user's specific work
- Candidate citations — BibTeX entries for papers worth citing (MUST verify against DBLP before presenting)
Citation Integrity
Every paper mentioned must have verified metadata:
- Author names: cross-check with DBLP or the paper's official page
- Venue and year: confirm against the published version (not preprint)
- Claims about results: only include numbers you can trace to a specific table/figure in the paper
- If uncertain about any detail, flag it explicitly rather than guessing
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: fcakyon
- Source: fcakyon/phd-skills
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.