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 mizukaizen/hive-doctrine-mcp --skill literature-synthesisgit clone --depth 1 https://github.com/mizukaizen/hive-doctrine-mcpWrote 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/mizukaizen/hive-doctrine-mcp/literature-synthesis)<a href="https://agentmods.dev/skills/mizukaizen/hive-doctrine-mcp/literature-synthesis"><img src="https://agentmods.dev/badge/skills/mizukaizen/hive-doctrine-mcp/literature-synthesis/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/mizukaizen/hive-doctrine-mcp/literature-synthesis"><img src="https://agentmods.dev/badge/skills/mizukaizen/hive-doctrine-mcp/literature-synthesis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00000 | $0.00544 |
| Opus 5.5 | $0.00000 | $0.00218 |
| Sonnet 5.5 | $0.00000 | $0.00109 |
| Haiku 4.5 | $0.00000 | $0.00054 |
Grade A, and why
literature-synthesis 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 2mo 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Literature Synthesis Skill
Use when synthesising research findings. Creates structured literature review with thematic analysis and gap identification.
When to Activate
- User asks for a "literature review", "research synthesis", or "evidence summary"
- The
/lit-reviewcommand is invoked - User asks to "summarise the evidence" or "what does the research say"
Process
-
Organise sources by theme. Group papers by their primary contribution to the research question. A single paper may appear in multiple themes if it addresses multiple aspects.
-
Within each theme, assess evidence strength:
- How many studies address this theme?
- What study designs were used? (RCTs carry more weight than observational studies)
- Do findings converge or diverge?
- What are the sample sizes?
- Are there methodological concerns?
-
Identify patterns:
- Convergence — Multiple studies with consistent findings. Note the conditions under which the finding holds.
- Divergence — Studies with contradictory findings. Investigate possible explanations: different populations, methods, outcome measures, time periods.
- Gaps — Questions that have not been studied, populations not represented, methods not applied.
-
Produce the synthesis document:
# Literature Synthesis: [Topic]
## Overview
[N] papers reviewed. [N] met inclusion criteria.
## Theme 1: [Name]
### Summary
[2-3 sentence overview of findings in this area]
### Evidence
| Study | Design | N | Key Finding | Quality |
|-------|--------|---|-------------|---------|
| Author (Year) | RCT | 200 | [Finding] | High |
### Assessment
Evidence strength: [Strong/Moderate/Weak/Insufficient]
Consistency: [Consistent/Mixed/Contradictory]
## Theme 2: [Name]
[Same structure]
## Gaps Identified
1. [Specific gap with explanation of why it matters]
2. [Specific gap]
## Implications for Current Study
[How these findings inform the research design and hypotheses]
- Quality control. Verify every cited finding traces to a specific source. Flag any claims that rest on a single study.
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.
- 2mo ago First seen · 66 lines · 0 tokens per session scan A 96ba3afedce9
literature-synthesis is a skill published in the GitHub repository mizukaizen/hive-doctrine-mcp (0 stars, last pushed 4mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 544 tokens. 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 2026-08-31.
literature-synthesis compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| literature-synthesismizukaizen/hive-doctrine-mcp | Skill | 0 | 4mo ago | MIT | A | 0 | Claude Code, Codex |
| paper-searchopenags/paper-search-mcp | Skill | 3.0k | 1mo ago | MIT | A | 62 | Claude Code, Codex |
| paper-searchopenags/paper-search-mcp | Skill | 3.0k | 1mo ago | MIT | A | 78 | Claude Code, Codex |
| songseegraniet/kheish | Skill | 213 | yesterday | Apache-2.0 | A | 42 | Claude Code, Codex |
| quantum-ground-statexi-zhao/OpenQuantum | Skill | 72 | yesterday | MIT | A | 103 | Codex |
| quantum-amplitude-estimationxi-zhao/OpenQuantum | Skill | 72 | yesterday | MIT | A | 63 | Claude Code, Codex |
| quantum-fermi-hubbard-vqexi-zhao/OpenQuantum | Skill | 72 | yesterday | MIT | A | 67 | Claude Code, Codex |