Agent skill

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…

Apache-2.0Auto-check passedResearch & Science

Install Consensus Interpret

skills CLI

$ npx skills add TianGzlab/OmicsClaw --skill consensus-interpret -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install TianGzlab/OmicsClaw consensus-interpret --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/spatial/consensus-interpret .claude/skills/consensus-interpret && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "consensus-interpret" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/consensus-interpret into .claude/skills/consensus-interpret/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "consensus-interpret", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/consensus-interpret

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add TianGzlab/OmicsClaw --skill consensus-interpret -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install TianGzlab/OmicsClaw consensus-interpret --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/spatial/consensus-interpret .agents/skills/consensus-interpret && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "consensus-interpret" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/consensus-interpret into .agents/skills/consensus-interpret/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "consensus-interpret", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add TianGzlab/OmicsClaw --skill consensus-interpret -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install TianGzlab/OmicsClaw consensus-interpret --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/spatial/consensus-interpret .cursor/skills/consensus-interpret && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "consensus-interpret" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/consensus-interpret into .cursor/skills/consensus-interpret/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "consensus-interpret", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/TianGzlab/OmicsClaw.git --path skills/spatial/consensus-interpret

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add TianGzlab/OmicsClaw --skill consensus-interpret -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install TianGzlab/OmicsClaw consensus-interpret --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/spatial/consensus-interpret .gemini/skills/consensus-interpret && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "consensus-interpret" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/consensus-interpret into .gemini/skills/consensus-interpret/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "consensus-interpret", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install TianGzlab/OmicsClaw consensus-interpret

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add TianGzlab/OmicsClaw --skill consensus-interpret -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/spatial/consensus-interpret .github/skills/consensus-interpret && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "consensus-interpret" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/consensus-interpret into .github/skills/consensus-interpret/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "consensus-interpret", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add TianGzlab/OmicsClaw --skill consensus-interpret -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install TianGzlab/OmicsClaw consensus-interpret --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/spatial/consensus-interpret .opencode/skills/consensus-interpret && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "consensus-interpret" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/consensus-interpret into .opencode/skills/consensus-interpret/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "consensus-interpret", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: consensus-interpret
GitHub stars: 161
Token cost: ~2k tokens
SKILL.md length: 456 words
Files: 36 (incl. references)
Skills in repo: 95
Repo updated: Jul 28, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

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…

Tasks that involve Citation management
SKILL.md covers When to use, Inputs & Outputs, Flow and Gotchas, plus 3 more sections
Runs Python scripts from its folder

What it does

Consensus Interpret is an agent skill from TianGzlab/OmicsClaw. 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 routing (use orchestrator).

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 37 other files, including reference files (for example `IMPLEMENTATION_PLAN.md`, `_artifacts.py` and `_candidates.py`).

It sits in Research & Science, covering Citation management. The repository describes itself as: Conversational & memory-enabled AI research partner for multi-omics analysis. CLI + Desktop App (installers in Releases). From biological idea to full research paper. The licence is Apache-2.0.

When your agent uses it

Tasks that involve Citation management

Example prompts

“/consensus-interpret”

Requirements

Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 6fbd79f. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships script files (Python, from the files we listed), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Consensus Interpret loads about 2k tokens when it runs, and up to ~3.2k if it reads all its reference files. Until then it costs about 92 tokens; SKILL.md has 456 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~92
When it runs · the whole SKILL.md, loaded when a task matches: ~2k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~3.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from TianGzlab/OmicsClaw at commit 6fbd79f, republished under its Apache-2.0 licence (© TianGzlab). 456 words, ~1,962 tokens.

Download SKILL.mdSave it as .claude/skills/consensus-interpret/SKILL.md (or your agent's skills folder). This skill also uses 35 other files; get the full folder from GitHub.

name: consensus-interpret
description: 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 routing (use orchestrator).
version: 0.1.0
author: OmicsClaw
license: Apache-2.0
tags: spatial, consensus, interpreted-layer, biology-annotation, marker-grounded, backward-proof-driven-recommendation
requires: anndata, numpy, pandas, scanpy, scikit-learn

consensus-interpret

When to use

The user has just finished a verified typed consensus run (consensus-domains or sc-consensus-clustering) and wants the next manual step (read cross_method_nmi.csv → run spatial-de → cross-reference markers → name cell types → decide downstream skill) done automatically with falsifiable evidence binding every LLM claim.

This skill does NOT replace the typed run. It is a strictly downstream consumer: it reads <typed_run_dir>/{plan.json, consensus_labels.tsv, member_scores.csv, cross_method_nmi.csv} plus the original adata, and writes its output to a different directory under analysis://interpreted/<typed_run_id>. The verified-vs-exploratory boundary established by ADR 0010 is preserved.

Skip when:

The typed run did not produce consensus_labels.tsv (i.e. consensus-domains exited non-zero — fix the typed run first).
You are looking for a generic query → skill dispatcher; use orchestrator for that (forward direction).
You want to refine the consensus itself based on LLM judgment; that is explicitly forbidden by §11.4 "LLM never participates in statistical merging" and would be rejected by this skill's T3 invariants.

Inputs & Outputs

<!-- AUTO-GENERATED from skill.yaml (interface) — do not edit by hand. Regenerate: python scripts/generate_skill_md.py <skill_dir> -->

Inputs

Input kinds: directory
File types: .json

Outputs

interpreted_report.md
interpreted_assignments.json
de_per_cluster.csv
contradiction_regions.csv
audit.json

Flow

1. Preflight (T1 — fail-fast if any fail)
   ├─ Load plan.json from --input; assert schema_version + typed run integrity
   ├─ Locate adata at plan.json.input_path (or --adata override); check exists
   ├─ Load consensus_labels.tsv; assert observation column ⊆ adata.obs.index
   ├─ Resolve marker DB:
   │    --markers <path> if given;
   │    else bundled `data/markers/panglaodb_<tissue>.tsv` for --tissue;
   │    else exit 5 (MarkerDBUnavailable)
   └─ If LLM required and unreachable AND --no-llm not set → exit 6 (LLMUnavailable)

2. Per-cluster differential expression (deterministic, scanpy)
   └─ scanpy.tl.rank_genes_groups(adata, groupby=consensus_<operator>, method='wilcoxon')
       → de_per_cluster.csv with top-K markers per cluster (K=20 default)

3. Marker → cell-type lookup (deterministic, pre-LLM)
   └─ For each cluster, compute candidate cell types by ranking DB entries
       whose gene appears in the cluster's top-K markers (weighted by db.weight × 1/de_rank).

4. LLM grounded interpretation (γ + β; one call per cluster + one synthesis call)
   ├─ Prompt template embeds (per cluster):
   │    cluster_id, n_cells, top-K DE markers,
   │    DB candidate cell types (ranked),
   │    member_agreement summary, cross_method_nmi neighbors
   ├─ LLM must return JSON conforming to interpreted_assignments.json
   │   schema; mandatory evidence.markers[] with non-empty
   │   {gene, db_source, db_celltype}
   └─ After all clusters: one synthesis call to produce next_steps[]
       with mandatory evidence_refs[] (capped at top-3 by priority)

5. Invariant enforcement (T3 — fail-fast if violated)
   ├─ Every cluster.evidence.markers != []      → else exit 7
   ├─ Every next_steps[*].evidence_refs != []   → else exit 7
   └─ Banner present and matches one of two allowed values → else exit 7

6. Coverage check (T2 — escalate to T1 if floor breached)
   └─ interpretable_cluster_frac < --coverage-floor → exit 8

7. Artifact writes
   ├─ interpreted_report.md (banner enforced in format_interpreted_report)
   ├─ interpreted_assignments.json
   ├─ de_per_cluster.csv
   ├─ contradiction_regions.csv
   └─ audit.json

Gotchas

It never refines the consensus. The LLM names cell types and recommends next steps but is forbidden from touching the statistical merge — the T3 invariants reject any attempt (ADR 0012 §11.4). Treat the consensus labels as fixed input.
Marker citations are mandatory. Every cluster's evidence.markers[] and every next-step's evidence_refs[] must be non-empty, or the run exits 7 (InvariantViolation). Ungrounded LLM output is rejected, not silently kept.
--no-llm changes the banner, not just the content. Structural-only mode emits [I-noLLM: ...] and drops all cell-type claims; downstream consumers must branch on the banner, not assume biology is present.
Output lands in a separate namespace. Interpreted artifacts go to analysis://interpreted/<run_id>, never overwriting the verified analysis://typed/<run_id> evidence base (the ADR 0010 boundary).

Show full SKILL.md (170 more words)Show less

Failure modes (per ADR 0012)

Exit	Name	Meaning
0	success	All clusters interpreted (or `low_confidence`), invariants intact, no degradation triggered
2	argparse	CLI error
3	TypedRunInvalid	`plan.json` missing / malformed / not from a typed run
4	AdataMismatch	adata `obs` index disjoint from `consensus_labels.tsv` `observation`
5	MarkerDBUnavailable	`--tissue` not in bundled DBs and `--markers` not provided
6	LLMUnavailable	LLM endpoint unreachable and `--no-llm` not given
7	InvariantViolation	LLM violated marker-grounding or evidence-ref contract (T3)
8	CoverageBelowThreshold	< 50% of clusters interpretable (after T2 degradation)

Key CLI

Default usage (after a typed run completes)

bash

oc run consensus-domains --input preprocessed.h5ad --output run1/ \
  --members banksy,graphst,leiden:resolution=0.5,leiden:resolution=1.0 \
  --non-interactive --operator kmode --seed 0

oc run consensus-interpret --input run1/ --output run1_interpreted/ \
  --tissue brain
# → run1_interpreted/interpreted_report.md begins with [A+I: ...]

CI / offline (structural-only)

bash

oc run consensus-interpret --input run1/ --output run1_struct/ \
  --tissue brain --no-llm
# → run1_struct/interpreted_report.md begins with [I-noLLM: ...]
# → no cell-type claims, only cluster sizes / NMI summary / contradiction regions

User-provided marker DB (non-bundled tissue)

bash

oc run consensus-interpret --input run1/ --output run1_interp/ \
  --markers ~/markers/mouse_intestine.tsv
# → bypasses --tissue requirement; uses user's custom DB

Files

SKILL.md and 35 other files (references) in skills/spatial/consensus-interpret of TianGzlab/OmicsClaw.

SKILL.md
IMPLEMENTATION_PLAN.md
_artifacts.py
_candidates.py
_de.py
_errors.py
_invariants.py
_llm.py
_marker_db.py
_metrics.py
_report.py
_run_reader.py
consensus_interpret.py
data/markers/README.md
data/markers/cellmarker_liver.tsv
data/markers/panglaodb_brain.tsv
data/markers/panglaodb_immune.tsv
data/markers/panglaodb_kidney.tsv
prompts
… and 17 more

Open the folder on GitHubat commit 6fbd79f

Compare with similar skills

Consensus Interpret next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Consensus Interpret compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Consensus Interpret this skillTianGzlab/OmicsClaw	161	—	~2k	Automated safety check: Pass	Apache-2.0	2 mo ago
Content Research Writerweapp-tailwindcss/weapp-tailwindcss	1.9k	25 repos	~3.5k	Automated safety check: Pass	MIT	today
NetworkxzLanqing/codex-claude-academic-skills	4.6k	16 repos	~3.2k	Automated safety check: Pass	BSD-3-Clause	4 mo ago
Citation Verification GuideGalaxy-Dawn/claude-scholar	5.7k	3 repos	~1.9k	Automated safety check: Pass	MIT	14 days ago
Systematic Review ScreenerImbad0202/academic-research-skills	51k	—	~8.4k	Automated safety check: Pass	Custom licence	4 days ago
Literature Reviewneflibata-feng/MyArxiv-Agent	126	21 repos	~5.9k	Automated safety check: Notes	MIT	3 days ago

Similar skills

Content Research Writer
weapp-tailwindcss/weapp-tailwindcss
Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section.
1.9k GitHub starsUsed in 25 repos~3.5k tokens
Research & ScienceAuto-check passed
Networkx
zLanqing/codex-claude-academic-skills
Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python.
4.6k GitHub starsUsed in 16 repos~3.2k tokens
Research & ScienceAuto-check passed
Citation Verification Guide
Galaxy-Dawn/claude-scholar
Reference guidance for checking every citation in academic writing against canonical sources such as DOI, arXiv, CrossRef and Semantic Scholar, to catch fake or wrong references.
5.7k GitHub starsUsed in 3 repos~1.9k tokens
Research & ScienceAuto-check passed
Systematic Review Screener
Imbad0202/academic-research-skills
Screens records for systematic, scoping and rapid reviews against fixed eligibility rules, using two blinded AI reviewers and a third adjudicator, with traceable PRISMA counts.
51k GitHub stars~8.4k tokensUpdated 4 days ago
Research & ScienceAuto-check passed
Literature Review
neflibata-feng/MyArxiv-Agent
Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.).
126 GitHub starsUsed in 21 repos~5.9k tokens
Research & ScienceAuto-check: notes
Openalex Database
neflibata-feng/MyArxiv-Agent
Query and analyze scholarly literature using the OpenAlex database.
126 GitHub starsUsed in 13 repos~3k tokens
Research & ScienceAuto-check passed

Questions about Consensus Interpret

What does Consensus Interpret do?

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…. Consensus Interpret is an agent skill from TianGzlab/OmicsClaw. 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.

When should I use Consensus Interpret?

Consensus Interpret fits situations like: tasks that involve Citation management.

How do I install Consensus Interpret in Claude Code?

Run `npx skills add TianGzlab/OmicsClaw --skill consensus-interpret -a claude-code`. Or copy the skill folder (skills/spatial/consensus-interpret in TianGzlab/OmicsClaw) into .claude/skills/consensus-interpret in your project. Claude Code loads it when a task matches its description.

How do I install Consensus Interpret in Codex?

Run `npx skills add TianGzlab/OmicsClaw --skill consensus-interpret -a codex`. Or copy the skill folder (skills/spatial/consensus-interpret in TianGzlab/OmicsClaw) into .agents/skills/consensus-interpret in your project. Codex loads it when a task matches its description.

Can I use Consensus Interpret in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add TianGzlab/OmicsClaw --skill consensus-interpret -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/consensus-interpret, .gemini/skills/consensus-interpret, .github/skills/consensus-interpret and .opencode/skills/consensus-interpret in your project.

What does Consensus Interpret need to run?

Going by SKILL.md and its folder, Consensus Interpret needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Consensus Interpret access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Consensus Interpret safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Consensus Interpret use?

Consensus Interpret is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Consensus Interpret use?

About 2k tokens (SKILL.md is roughly 7.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.3k tokens, read only when the agent opens those files.

What are the alternatives to Consensus Interpret?

Skills that share tags, products or a category with Consensus Interpret: Content Research Writer (weapp-tailwindcss/weapp-tailwindcss, 1.9k stars), Networkx (zLanqing/codex-claude-academic-skills, 4.6k stars), Citation Verification Guide (Galaxy-Dawn/claude-scholar, 5.7k stars) and Systematic Review Screener (Imbad0202/academic-research-skills, 51k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Consensus Interpret?

TianGzlab (a GitHub organization) maintains it in TianGzlab/OmicsClaw, which has 161 GitHub stars. The repository holds 95 skills in this directory. The repository was last updated on July 28, 2026.

Source: TianGzlab/OmicsClaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Consensus Interpret

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

consensus-interpret

When to use

Inputs & Outputs

Flow

Gotchas

Failure modes (per ADR 0012)

Key CLI

Default usage (after a typed run completes)

CI / offline (structural-only)

User-provided marker DB (non-bundled tissue)

See also

Files

Compare with similar skills

Similar skills

More from TianGzlab/OmicsClaw

Related

Questions about Consensus Interpret