full-text-search

full-text-search is a skill for Claude Code from sparq-org/sparq. It costs 66 tokens per session (6,279 once invoked), scanned A, original, MIT.

An optional full-text search layer for RDF string values, similar to searching words in documents. It provides a BM25 index for relevance-ranked results and SPARQL predicates for keyword, prefix, phrase, proximity, and optional typo-tolerant searches.

In plain words
What is it for?
Use it to search titles, descriptions, labels, and other string literals, rank matching entities, search phrases or nearby words, and provide entity or IRI prefix completion.
Why use it?
It adds text search to graph queries without putting search code into the core engine or browser bundle. It can also support autocomplete for labels and identifiers.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is sparq-core = { path = "../sparq-core" }.

Part of the sparq plugin — 55 skills, 20 agents, 2 hooks shipped together

Good fit Use it to search titles, descriptions, labels, and other string literals, rank matching entities, search phrases or nearby words, and provide entity or IRI prefix completion.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/sparq-org/sparq
agentmods
npx agentmods add skills/sparq-org/sparq/full-text-search

Made for: Claude Code.

Or install sparq, the plugin that ships this one along with the rest of its 55 skills, 20 agents, 2 hooks.

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 full-text-search

README.md
[![agentmods](https://agentmods.dev/badge/skills/sparq-org/sparq/full-text-search/github.svg)](https://agentmods.dev/skills/sparq-org/sparq/full-text-search)
Your own site
<a href="https://agentmods.dev/skills/sparq-org/sparq/full-text-search"><img src="https://agentmods.dev/badge/skills/sparq-org/sparq/full-text-search/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 full-text-search

Your own site · 80×15
<a href="https://agentmods.dev/skills/sparq-org/sparq/full-text-search"><img src="https://agentmods.dev/badge/skills/sparq-org/sparq/full-text-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 66 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,279 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00066 $0.06279
Opus 5 $0.00033 $0.03139
Sonnet 5 $0.00013 $0.01256
Haiku 4.5 $0.00007 $0.00628

Measured 10d ago against content hash 564ec05b90b0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

full-text-search 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 10d 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.

skills/full-text-search/SKILL.md · 202 lines

How it starts

The opening of the file, as written. The whole thing — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.

sparq full-text search (sparq-text)

sparq-text is an opt-in, separate crate that adds full-text search over the string literals of a sparq Graph. It gives you two surfaces: a low-level owned BM25 inverted index (TextIndex) keyed by dictionary term id, and text: magic predicates that you write inside ordinary SPARQL and that query_text rewrites into inline VALUES over the index's hits. The engine, planner, and the lean sparq-wasm bundle carry zero text-search code — full-text support exists only when you depend on sparq-text (or load its dedicated tier-b sparq-text-wasm browser bundle; see below).

Quickstart

Cargo.toml:

[dependencies]
sparq-core = { path = "../sparq-core" }
sparq-text = { path = "../sparq-text" }   # default features: ["engine", "parallel"]
use sparq_core::Graph;
use sparq_text::{query_text, TextIndex};

let g = Graph::load_str(r#"
    <http://ex/post1> <http://ex/title> "The quick brown fox" .
    <http://ex/post2> <http://ex/title> "Fox hunting banned" .
"#, "ntriples").unwrap();

// 1. Library-level: build the BM25 index (one dict scan), search returns Hit { id, score }.
let index = TextIndex::build(&g);
for hit in index.search("quick fox") {          // AND of tokens, BM25 best-first
    let literal = g.dict.term(hit.id);           // hit.id IS the dict id of the literal
    println!("{literal} (bm25 {})", hit.score);
}

// 2. SPARQL-level: text: magic predicates, rewritten + executed by the engine.
let r = query_text(&g, r#"
    PREFIX text: <http://sparq.dev/text#>
    SELECT ?post ?s WHERE {
      ?post  <http://ex/title> ?title .
      ?title text:matches "fox" .
      ?title text:score   ?s .
    } ORDER BY DESC(?s)"#, &index).unwrap();
assert_eq!(r.rows.len(), 2);                     // r.rows: Vec<Vec<Option<oxrdf::Term>>>, r.vars

The dictionary term id of a string literal is its document id, so search results join back to subjects/predicates through the store's ordinary permutation indexes — that join is what the SPARQL surrounding the magic pattern does.

Read the full file on GitHub · 202 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. 10d ago First seen · 202 lines · 66 tokens per session scan A 564ec05b90b0

Subscribe to this mod's changes

full-text-search is a skill published in the GitHub repository sparq-org/sparq (12 stars, last pushed yesterday), licensed MIT. It adds 66 tokens to every session and 6,279 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 2026-08-31.

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