Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add fcakyon/phd-skills --skill literature-researchgit clone --depth 1 https://github.com/fcakyon/phd-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/fcakyon/phd-skills/literature-research)<a href="https://agentmods.dev/skills/fcakyon/phd-skills/literature-research"><img src="https://agentmods.dev/badge/skills/fcakyon/phd-skills/literature-research/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/fcakyon/phd-skills/literature-research"><img src="https://agentmods.dev/badge/skills/fcakyon/phd-skills/literature-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00065 | $0.00882 |
| Opus 5 | $0.00032 | $0.00441 |
| Sonnet 5 | $0.00013 | $0.00176 |
| Haiku 4.5 | $0.00006 | $0.00088 |
Grade A, and why
literature-research scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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?)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 97 lines · 65 tokens per session scan A 1bd388d1839b
literature-research is a skill published in the GitHub repository fcakyon/phd-skills (394 stars, last pushed 2mo ago), licensed MIT. It adds 65 tokens to every session and 882 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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