build-text-network

build-text-network is a skill for Claude Code, Codex from MattArtzAnthro/gephi-ai. It costs 54 tokens per session (682 once invoked), scanned A, original, Apache-2.0.

A method for turning a collection of text into a graph of words that appear near one another. Gephi is software for exploring and laying out such graphs; the connections show textual proximity, not proven meaning.

In plain words
What is it for?
Use it with transcripts, field notes, survey responses, documents, or social posts to build a concept map, inspect discourse, and visualize themes.
Why use it?
It helps reveal recurring themes and relationships without relying only on manual reading or generic stopword lists.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it with transcripts, field notes, survey responses, documents, or social posts to build a concept map, inspect discourse, and visualize themes.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/mattartzanthro/gephi-ai/build-text-network
Install

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.

Any agent
npx skills add MattArtzAnthro/gephi-ai --skill build-text-network
Clone the repo
git clone --depth 1 https://github.com/MattArtzAnthro/gephi-ai

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for build-text-network

README.md
[![agentmods](https://agentmods.dev/badge/skills/mattartzanthro/gephi-ai/build-text-network/github.svg)](https://agentmods.dev/skills/mattartzanthro/gephi-ai/build-text-network)
Your own site
<a href="https://agentmods.dev/skills/mattartzanthro/gephi-ai/build-text-network"><img src="https://agentmods.dev/badge/skills/mattartzanthro/gephi-ai/build-text-network/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.

agentmods 80×15 button for build-text-network

Your own site · 80×15
<a href="https://agentmods.dev/skills/mattartzanthro/gephi-ai/build-text-network"><img src="https://agentmods.dev/badge/skills/mattartzanthro/gephi-ai/build-text-network.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 54 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 682 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00054 $0.00682
Opus 5 $0.00027 $0.00341
Sonnet 5 $0.00011 $0.00136
Haiku 4.5 $0.00005 $0.00068

Measured 9d ago against content hash 6750846f48ab, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

build-text-network 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 9d 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.

plugins/gephi-network-analysis/skills/build-text-network/SKILL.md · 62 lines

How it starts

The opening of the file, as written. The whole thing — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Build a Text Network

Build and tune a word co-occurrence graph whose vocabulary reflects the corpus rather than stopwords or collection artifacts. A co-occurrence edge represents proximity in text, not semantic truth.

Read ../gephi/references/text-network-analysis.md before choosing construction parameters and ../gephi/references/layout-guide.md before laying out the result. If the request does not contain text or a readable path, ask for one.

Construction Choices

Use gephi_text_to_network. Record the final values and why they were chosen:

  • text: prefer a list when the corpus has natural segments; the window resets per item and avoids cross-document edges;
  • window_size: smaller captures tighter pairings, larger captures looser themes;
  • extra_stopwords: remove corpus-specific filler, names, and boilerplate;
  • pos_filter: use nouns or proper nouns for a concept-focused map when suitable;
  • min_word_frequency and min_edge_weight: raise these to remove rare noise;
  • merge_phrases: combine useful repeated bigrams;
  • exclude_self_referential and self_referential_threshold: remove words that occur in nearly every document;
  • context_snippets: preserve examples needed for later interpretation.

Build-and-Tune Loop

  1. Call gephi_health_check. If it fails, tell the user to start Gephi and stop.
  2. Build once with sensible parameters for this corpus. Run gephi_get_graph_stats, gephi_profile_graph, and gephi_visual_qa.
  3. Inspect top-degree words with gephi_query_nodes. If hubs are interviewer names, filler, boilerplate, or other artifacts, rebuild with clear_existing: true and improved stopwords, part-of-speech filtering, or frequency floors.
  4. Repeat the vocabulary check until substantive terms dominate. Rebuild from parameters; do not hand-delete noisy nodes.
  5. Compute modularity, color by community, size by degree, and apply neutral edge styling appropriate for a dense co-occurrence graph.
  6. Run ForceAtlas 2 and Noverlap according to the layout guide. Perform the full gephi_visual_qa and one-variable-at-a-time adjustment loop.
  7. Export a PNG where requested and offer gephi_view_graph when MCP Apps are supported.

Read the full file on GitHub · 62 lines

Changes

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.

  1. 9d ago First seen · 62 lines · 54 tokens per session scan A 6750846f48ab

Subscribe to this mod's changes

build-text-network is a skill published in the GitHub repository MattArtzAnthro/gephi-ai (22 stars, last pushed 8d ago), licensed Apache-2.0. It adds 54 tokens to every session and 682 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.

Related

Other skills, from other repositories

cuopt-numerical-optimization-formulation

LP, MILP, QP — concepts, problem-text parsing, and formulation patterns (parameters, constraints, decisions, objective). Concepts only; no API.

NVIDIA/skills · 42 tokens

earth2studio-create-datasource

Create and validate Earth2Studio data source wrappers (DataSource, ForecastSource, DataFrameSource, ForecastFrameSource) from remote stores. Do NOT use for fetching data with existing sources, model inference, or installation tasks.

NVIDIA/skills · 53 tokens

earth2studio-data-fetch

Fetch weather/climate data via Earth2Studio data sources for specific variables and times. Do NOT use for inference pipelines, model discovery, or installation.

NVIDIA/skills · 36 tokens

i4h-workflow-dataset-convert

Convert workflow HDF5 recordings to LeRobot datasets for training or browser inspection. Use for conversion; do not use for replay, augmentation, or raw-data repair.

NVIDIA/skills · 43 tokens

i4h-catheter-navigation-e2e

End-to-end smoke for catheter navigation covering setup, digital twin, DRR, and unit tests. Use when asked to run the full catheter workflow smoke or demo the v0.7 pipeline.

NVIDIA/skills · 49 tokens

medtech-model-evidence-export

Exports sanitized metadata, parameters, reproducibility details, quality metrics, and optional review artifacts from Medical AI inference runs or evidence packs to MLflow. Use after inference, including NV-Generate runs; not for live training tracking, model registration, or clinical use.

NVIDIA/skills · 59 tokens