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 Azealoo/miniAgent --skill literature_consensus_mapgit clone --depth 1 https://github.com/Azealoo/miniAgentWrote 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/azealoo/miniagent/literature_consensus_map)<a href="https://agentmods.dev/skills/azealoo/miniagent/literature_consensus_map"><img src="https://agentmods.dev/badge/skills/azealoo/miniagent/literature_consensus_map.svg" alt="Measured on agentmods" 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 | $0.00024 | $0.00587 |
| Opus 5 | $0.00012 | $0.00293 |
| Sonnet 5 | $0.00005 | $0.00117 |
| Haiku 4.5 | $0.00002 | $0.00059 |
Grade A, and why
literature_consensus_map 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 8d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 8d ago First seen · 60 lines · 24 tokens per session scan A 35cd7eef12e0
literature_consensus_map is a skill published in the GitHub repository Azealoo/miniAgent (2 stars, last pushed 2mo ago), with no licence file. It adds 24 tokens to every session and 587 once invoked, about $0.0001 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 2026-08-31.
Other skills, from other repositories
ClinicalTrials.gov Disease Landscape Scanner
Skill "ClinicalTrials.gov Disease Landscape Scanner" from TianGzlab/OmicsClaw, covering clinicaltrials.gov disease landscape scanner, when to use this skill, installation, inputs and outputs.
Preclinical Literature Extraction
Search Consensus (consensus.app) for preclinical studies on a molecular target in a disease, then extract structured in vitro and in vivo experiment details from each paper.
consensus-interpret
Load when biologically interpreting a finished verified consensus run (consensus-domains / sc-consensus-clustering) — inline DE, marker-DB lookup, and LLM cell-type naming with mandatory marker citations + evidence-bound next-step recommendations. Skip when the consensus run failed (fix it first); forward query→skill…
sc-consensus-integration
Load when you want a multi-sample single-cell (scRNA) clustering robust to the choice of integration method — fanning out Harmony/Scanorama/scVI + an unintegrated baseline, scoring each by a batch-mixing intrinsic panel, and voting a consensus. Skip when single-batch (use sc-consensus-clustering); one integration…
consensus-domains
Load when you want a verified multi-method consensus over spatial tissue domains on a preprocessed spatial AnnData — fanning out N domain methods, ranking base clusterings, and emitting a typed consensus with cross-method disagreement. Skip when one method suffices (use spatial-domains); the data is single-cell (use…
sc-integrate-cluster
Load when running a single batch-correction representation (none/Harmony/Scanorama/scVI) + clustering of single-cell data as one self-contained unit — normally fanned out as a member of sc-consensus-integration. Skip when you want the full integration consensus (use sc-consensus-integration); resolution-robust…